diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml new file mode 100644 index 0000000..c3ddf03 --- /dev/null +++ b/.github/workflows/tests.yml @@ -0,0 +1,52 @@ +name: Tests + +on: + pull_request: + schedule: + - cron: "0 7 * * 1" # Every Monday at 07:00 UTC + +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + +jobs: + test: + name: Test (${{ matrix.os }}, Python ${{ matrix.python-version }}) + runs-on: ${{ matrix.os }} + permissions: + contents: read + id-token: write # required for OIDC tokenless Codecov upload + strategy: + fail-fast: false + matrix: + os: [ubuntu-latest, macos-latest, windows-latest] + python-version: ["3.13"] + + steps: + - uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4 + with: + persist-credentials: false + + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 + with: + python-version: ${{ matrix.python-version }} + + - name: Install package and test dependencies + run: pip install -e ".[test]" + + - name: Run tests + if: matrix.os != 'ubuntu-latest' + run: pytest + + - name: Run tests with coverage + if: matrix.os == 'ubuntu-latest' + run: pytest --cov=ragone --cov-report=xml + + - name: Upload coverage to Codecov + if: matrix.os == 'ubuntu-latest' + uses: codecov/codecov-action@0fb7174895f61a3b6b78fc075e0cd60383518dac # v5 + with: + files: coverage.xml + fail_ci_if_error: true + use_oidc: true diff --git a/.gitignore b/.gitignore index e1cb1de..fef8d68 100644 --- a/.gitignore +++ b/.gitignore @@ -25,3 +25,6 @@ slurm/ # Ignore debug files debug*.py debug*.ipynb + +# Ignore agents files +.github/agents/ diff --git a/figures/aged_solution_evolution_vf.png b/figures/aged_solution_evolution_vf.png index 795eb9b..9e376db 100644 Binary files a/figures/aged_solution_evolution_vf.png and b/figures/aged_solution_evolution_vf.png differ diff --git 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line-length = 88 + +[tool.pytest.ini_options] +testpaths = ["tests"] +markers = [ + "unit: fast, isolated unit tests", + "integration: slower end-to-end tests", +] + +[tool.coverage.run] +source = ["ragone"] +omit = ["tests/*"] + +[tool.coverage.report] +show_missing = true diff --git a/run_all.sh b/run_all.sh index e2ca65f..73ee4ce 100644 --- a/run_all.sh +++ b/run_all.sh @@ -1,4 +1,4 @@ -sbatch slurm/ragone_ageing_parallel.slurm +sbatch slurm/ragone_ageing.slurm sbatch slurm/ragone_compare.slurm sbatch slurm/ragone_parameters.slurm -sbatch slurm/rate_capability.slurm +sbatch slurm/rpt.slurm diff --git a/scripts/rpt.py b/scripts/rpt.py index 184d0d6..71e7c49 100644 --- a/scripts/rpt.py +++ b/scripts/rpt.py @@ -58,8 +58,8 @@ ageing_solutions = [aged_sol.all_first_states[i] for i in cycles] value_ranges = { - "power": [2, 10, 18, 26, 34, 42, 50], - # "power": [2, 6, 10, 14, 18], + # "power": [2, 10, 18, 26, 34, 42, 50], + "power": [2, 6, 10, 14, 18], # "current": [0.5, 1.25, 2.5, 3.75, 5], } @@ -99,5 +99,5 @@ ymax = 20 if mode == "power" else 5 ax.set_ylim(0, ymax * 1.1) ax.legend(fontsize=10) - fig.savefig(ROOT / "figures" / f"rate_capability_{mode}{tag}.png", dpi=300) + fig.savefig(ROOT / "figures" / f"rpt_{mode}{tag}.png", dpi=300) print("Saved figure for mode:", mode) diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/conftest.py b/tests/conftest.py new file mode 100644 index 0000000..ad99c10 --- /dev/null +++ b/tests/conftest.py @@ -0,0 +1,71 @@ +import matplotlib + +matplotlib.use("Agg") +import matplotlib.pyplot as plt + +import numpy as np +import pytest +from unittest.mock import MagicMock + +# Minimal parameter values that satisfy RagoneSimulation.__init__ +# without needing a real pybamm.ParameterValues object. +PARAM_VALUES = { + "Nominal cell capacity [A.h]": 5.0, + "Upper voltage cut-off [V]": 4.2, + "Lower voltage cut-off [V]": 2.5, +} + + +@pytest.fixture(autouse=True) +def close_plots(): + """Close all matplotlib figures after every test to prevent memory leaks.""" + yield + plt.close("all") + + +@pytest.fixture +def param_values(): + """Return a fresh copy of the minimal parameter dict.""" + return dict(PARAM_VALUES) + + +@pytest.fixture +def mock_model(param_values): + """Return a MagicMock that mimics a pybamm model's essential attributes.""" + model = MagicMock() + model.default_parameter_values = param_values + model.default_solver = MagicMock() + model.default_var_pts = {} + return model + + +@pytest.fixture +def power_data(): + return { + "Power [W]": np.array([1.0, 5.0, 10.0, 50.0]), + "Energy [W.h]": np.array([20.0, 18.0, 15.0, 8.0]), + "Time [h]": np.array([20.0, 3.6, 1.5, 0.16]), + } + + +@pytest.fixture +def power_solution(power_data): + from ragone.solution import RagoneSolution + + return RagoneSolution(power_data, "power") + + +@pytest.fixture +def current_data(): + return { + "Current [A]": np.array([1.0, 2.0, 5.0, 10.0]), + "Capacity [A.h]": np.array([5.0, 4.8, 4.2, 3.5]), + "Time [h]": np.array([5.0, 2.4, 0.84, 0.35]), + } + + +@pytest.fixture +def current_solution(current_data): + from ragone.solution import RagoneSolution + + return RagoneSolution(current_data, "current") diff --git a/tests/integration/__init__.py b/tests/integration/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/unit/test_plotting.py b/tests/unit/test_plotting.py new file mode 100644 index 0000000..4d64e5a --- /dev/null +++ b/tests/unit/test_plotting.py @@ -0,0 +1,173 @@ +"""Unit tests for RagonePlot.""" + +import matplotlib.axes +import matplotlib.figure +import numpy as np +import pytest + +from ragone.solution import RagoneSolution +from ragone.plotting import RagonePlot + + +# --------------------------------------------------------------------------- +# Fixtures +# --------------------------------------------------------------------------- + + +@pytest.fixture +def power_plot(power_solution): + return RagonePlot(power_solution) + + +@pytest.fixture +def current_solution_with_watts(current_data): + """current solution that also carries Power/Energy keys (convert_to_watts).""" + data = dict(current_data) + data["Power [W]"] = np.array([3.7, 7.4, 18.5, 37.0]) + data["Energy [W.h]"] = np.array([18.5, 17.8, 15.6, 13.0]) + return RagoneSolution(data, "current") + + +# --------------------------------------------------------------------------- +# __init__ +# --------------------------------------------------------------------------- + + +class TestRagonePlotInit: + @pytest.mark.unit + def test_single_solution_wrapped_in_list(self, power_solution): + plot = RagonePlot(power_solution) + assert plot.solutions == [power_solution] + + @pytest.mark.unit + def test_list_of_solutions_stored_unchanged(self, power_solution): + plot = RagonePlot([power_solution]) + assert plot.solutions == [power_solution] + + @pytest.mark.unit + def test_mode_set_from_power_solution(self, power_solution): + assert RagonePlot(power_solution).mode == "power" + + @pytest.mark.unit + def test_mode_set_from_current_solution(self, current_solution): + assert RagonePlot(current_solution).mode == "current" + + @pytest.mark.unit + def test_input_output_labels_for_power(self, power_solution): + plot = RagonePlot(power_solution) + assert plot.input == "Power [W]" + assert plot.output == "Energy [W.h]" + + @pytest.mark.unit + def test_input_output_labels_for_current(self, current_solution): + plot = RagonePlot(current_solution) + assert plot.input == "Current [A]" + assert plot.output == "Capacity [A.h]" + + @pytest.mark.unit + def test_invalid_scale_raises_value_error(self, power_solution): + with pytest.raises(ValueError, match="scale must be either"): + RagonePlot(power_solution, scale="semilog") + + @pytest.mark.unit + def test_mixed_modes_without_watt_keys_raises( + self, power_solution, current_solution + ): + with pytest.raises(ValueError, match="same mode or have"): + RagonePlot([power_solution, current_solution]) + + @pytest.mark.unit + def test_mixed_modes_with_watt_keys_uses_power_mode( + self, power_solution, current_solution_with_watts + ): + plot = RagonePlot([power_solution, current_solution_with_watts]) + assert plot.mode == "power" + assert plot.input == "Power [W]" + + @pytest.mark.unit + def test_labels_stored(self, power_solution): + plot = RagonePlot(power_solution, labels=["test"]) + assert plot.labels == ["test"] + + +# --------------------------------------------------------------------------- +# _compute_data_limits +# --------------------------------------------------------------------------- + + +class TestRagonePlotDataLimits: + @pytest.mark.unit + def test_limits_from_single_solution(self, power_solution): + # power_data: Power [1,5,10,50], Energy [20,18,15,8] + plot = RagonePlot(power_solution) + assert plot.min_input == pytest.approx(1.0) + assert plot.max_input == pytest.approx(50.0) + assert plot.min_output == pytest.approx(8.0) + assert plot.max_output == pytest.approx(20.0) + + @pytest.mark.unit + def test_limits_span_all_solutions(self, power_solution, power_data): + wider_data = { + "Power [W]": np.array([0.5, 100.0]), + "Energy [W.h]": np.array([25.0, 5.0]), + "Time [h]": np.array([50.0, 0.05]), + } + wider_sol = RagoneSolution(wider_data, "power") + plot = RagonePlot([power_solution, wider_sol]) + assert plot.min_input == pytest.approx(0.5) + assert plot.max_input == pytest.approx(100.0) + assert plot.min_output == pytest.approx(5.0) + assert plot.max_output == pytest.approx(25.0) + + +# --------------------------------------------------------------------------- +# Helper methods +# --------------------------------------------------------------------------- + + +class TestRagonePlotHelpers: + @pytest.mark.unit + def test_get_ticks_range_one_decade(self, power_plot): + assert power_plot._get_ticks_range(1.0, 10.0) == [1, 2, 5, 10] + + @pytest.mark.unit + def test_get_ticks_range_two_decades(self, power_plot): + assert power_plot._get_ticks_range(1.0, 100.0) == [1, 2, 5, 10, 20, 50, 100] + + @pytest.mark.unit + def test_format_tick_labels_integers(self, power_plot): + assert power_plot._format_tick_labels([1, 2, 10]) == ["1", "2", "10"] + + @pytest.mark.unit + def test_format_tick_labels_mixed(self, power_plot): + # 1.0 → "1" (int-valued float), 0.5 and 2.5 → str of float + assert power_plot._format_tick_labels([0.5, 1.0, 2.5]) == ["0.5", "1", "2.5"] + + +# --------------------------------------------------------------------------- +# plot() +# --------------------------------------------------------------------------- + + +class TestRagonePlotPlot: + @pytest.mark.unit + def test_returns_figure_and_axes(self, power_plot): + fig, ax = power_plot.plot(show_plot=False) + assert isinstance(fig, matplotlib.figure.Figure) + assert isinstance(ax, matplotlib.axes.Axes) + + @pytest.mark.unit + def test_linear_scale_returns_figure(self, power_solution): + fig, ax = RagonePlot(power_solution, scale="linear").plot(show_plot=False) + assert isinstance(fig, matplotlib.figure.Figure) + + @pytest.mark.unit + def test_labels_produce_a_legend(self, power_solution): + fig, ax = RagonePlot(power_solution, labels=["Series A"]).plot(show_plot=False) + assert ax.get_legend() is not None + + @pytest.mark.unit + def test_no_labels_produces_no_legend(self, power_plot): + # Default (labels=None) → skip_legend=True → no legend drawn + _, ax = power_plot.plot(show_plot=False) + assert ax.get_legend() is None diff --git a/tests/unit/test_simulation.py b/tests/unit/test_simulation.py new file mode 100644 index 0000000..2ca86f7 --- /dev/null +++ b/tests/unit/test_simulation.py @@ -0,0 +1,267 @@ +"""Unit tests for RagoneSimulation. + +pybamm.Simulation and pybamm.Experiment are mocked so no actual solver runs +occur. Only the constructor (which calls pybamm.step.VoltageTermination) and +the public API surface are exercised here. +""" + +import numpy as np +import pybamm +import pytest +from unittest.mock import MagicMock, patch + +from ragone.simulation import RagoneSimulation +from ragone.solution import RagoneSolution + + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + + +def _mock_pybamm_sol(time_final: float = 1.0, energy_final: float = 10.0) -> MagicMock: + """Return a MagicMock that behaves like a pybamm Solution for the keys + used by RagoneSimulation.solve().""" + sol = MagicMock() + + def _getitem(key): + m = MagicMock() + if key == "Time [h]": + m.entries = np.array([0.0, time_final]) + elif key == "Discharge energy [W.h]": + m.entries = np.array([0.0, energy_final]) + else: + m.entries = np.array([0.0, 1.0]) + return m + + sol.__getitem__.side_effect = _getitem + return sol + + +# --------------------------------------------------------------------------- +# __init__ tests +# --------------------------------------------------------------------------- + + +class TestRagoneSimulationInit: + """Tests for attribute initialisation — no pybamm solver calls.""" + + @pytest.mark.unit + def test_power_mode_sets_input_output(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0]) + assert sim.input == "Power [W]" + assert sim.output == "Energy [W.h]" + + @pytest.mark.unit + def test_power_mode_assigns_pybamm_step_fun(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0]) + assert sim.step_fun is pybamm.step.power + + @pytest.mark.unit + def test_power_mode_ref_value(self, mock_model): + # ref_value = capacity * (V_upper + V_lower) / 2 + # = 5.0 * (4.2 + 2.5) / 2 = 16.75 + sim = RagoneSimulation(mock_model, [1.0]) + assert sim.ref_value == pytest.approx(5.0 * (4.2 + 2.5) / 2) + + @pytest.mark.unit + def test_current_mode_sets_input_output(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0], mode="current") + assert sim.input == "Current [A]" + assert sim.output == "Capacity [A.h]" + + @pytest.mark.unit + def test_current_mode_assigns_pybamm_step_fun(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0], mode="current") + assert sim.step_fun is pybamm.step.current + + @pytest.mark.unit + def test_current_mode_ref_value_equals_nominal_capacity(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0], mode="current") + assert sim.ref_value == pytest.approx(5.0) + + @pytest.mark.unit + def test_invalid_mode_raises_value_error(self, mock_model): + with pytest.raises(ValueError, match="mode must be either"): + RagoneSimulation(mock_model, [1.0], mode="invalid") + + @pytest.mark.unit + def test_discharge_direction_sets_positive_sign(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0], direction="discharge") + assert sim.sign == 1 + + @pytest.mark.unit + def test_charge_direction_sets_negative_sign(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0], direction="charge") + assert sim.sign == -1 + + @pytest.mark.unit + def test_invalid_direction_raises_value_error(self, mock_model): + with pytest.raises(ValueError, match="Invalid `direction`"): + RagoneSimulation(mock_model, [1.0], direction="sideways") + + @pytest.mark.unit + def test_falls_back_to_model_parameter_values(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0]) + assert sim.parameter_values is mock_model.default_parameter_values + + @pytest.mark.unit + def test_explicit_parameter_values_override_model_defaults( + self, mock_model, param_values + ): + custom = dict(param_values) + sim = RagoneSimulation(mock_model, [1.0], parameter_values=custom) + assert sim.parameter_values is custom + assert sim.parameter_values is not mock_model.default_parameter_values + + @pytest.mark.unit + def test_falls_back_to_model_solver(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0]) + assert sim.solver is mock_model.default_solver + + @pytest.mark.unit + def test_explicit_solver_overrides_model_default(self, mock_model): + custom_solver = MagicMock() + sim = RagoneSimulation(mock_model, [1.0], solver=custom_solver) + assert sim.solver is custom_solver + + @pytest.mark.unit + def test_falls_back_to_model_var_pts(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0]) + assert sim.var_pts is mock_model.default_var_pts + + @pytest.mark.unit + def test_explicit_var_pts_overrides_model_default(self, mock_model): + custom_var_pts = {"x_n": 20} + sim = RagoneSimulation(mock_model, [1.0], var_pts=custom_var_pts) + assert sim.var_pts is custom_var_pts + + @pytest.mark.unit + def test_value_range_is_stored(self, mock_model): + value_range = [1.0, 2.0, 5.0] + sim = RagoneSimulation(mock_model, value_range) + assert sim.value_range is value_range + + @pytest.mark.unit + def test_convert_to_watts_defaults_to_false(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0]) + assert sim.convert_to_watts is False + + @pytest.mark.unit + def test_convert_to_watts_can_be_enabled(self, mock_model): + sim = RagoneSimulation(mock_model, [1.0], convert_to_watts=True) + assert sim.convert_to_watts is True + + +# --------------------------------------------------------------------------- +# solve() tests +# --------------------------------------------------------------------------- + + +class TestRagoneSimulationSolve: + """Tests for solve() with pybamm.Simulation and pybamm.Experiment mocked.""" + + @pytest.fixture + def sim(self, mock_model): + s = RagoneSimulation(mock_model, [5.0, 10.0]) + s.step_fun = MagicMock(return_value=MagicMock()) + return s + + @pytest.fixture + def sim_current_watts(self, mock_model): + s = RagoneSimulation(mock_model, [2.0], mode="current", convert_to_watts=True) + s.step_fun = MagicMock(return_value=MagicMock()) + return s + + @pytest.mark.unit + def test_returns_ragone_solution(self, sim): + mock_sol = _mock_pybamm_sol(time_final=1.0) + with ( + patch.object(sim, "_compute_theoretical_value", return_value=50.0), + patch("pybamm.Experiment"), + patch("pybamm.Simulation") as MockSim, + ): + MockSim.return_value.solve.return_value = mock_sol + result = sim.solve() + assert isinstance(result, RagoneSolution) + + @pytest.mark.unit + def test_stores_solution_on_self(self, sim): + mock_sol = _mock_pybamm_sol(time_final=1.0) + with ( + patch.object(sim, "_compute_theoretical_value", return_value=50.0), + patch("pybamm.Experiment"), + patch("pybamm.Simulation") as MockSim, + ): + MockSim.return_value.solve.return_value = mock_sol + result = sim.solve() + assert sim.solution is result + + @pytest.mark.unit + def test_solution_mode_matches_simulation_mode(self, sim): + mock_sol = _mock_pybamm_sol(time_final=1.0) + with ( + patch.object(sim, "_compute_theoretical_value", return_value=50.0), + patch("pybamm.Experiment"), + patch("pybamm.Simulation") as MockSim, + ): + MockSim.return_value.solve.return_value = mock_sol + result = sim.solve() + assert result.mode == "power" + + @pytest.mark.unit + def test_solver_error_produces_nan_entries(self, sim): + with ( + patch.object(sim, "_compute_theoretical_value", return_value=50.0), + patch("pybamm.Experiment"), + patch("pybamm.Simulation") as MockSim, + ): + MockSim.return_value.solve.side_effect = pybamm.SolverError("boom") + result = sim.solve() + assert np.all(np.isnan(result.data["Power [W]"])) + assert np.all(np.isnan(result.data["Energy [W.h]"])) + + @pytest.mark.unit + def test_stops_early_when_output_below_threshold(self, mock_model): + """solve() breaks out of the loop when output < 10 % of theoretical.""" + # value=5.0, time_final=0.001 → output=0.005 < 0.1*50.0=5.0 → break + sim = RagoneSimulation(mock_model, [5.0, 10.0, 20.0]) + sim.step_fun = MagicMock(return_value=MagicMock()) + mock_sol = _mock_pybamm_sol(time_final=0.001) + with ( + patch.object(sim, "_compute_theoretical_value", return_value=50.0), + patch("pybamm.Experiment"), + patch("pybamm.Simulation") as MockSim, + ): + MockSim.return_value.solve.return_value = mock_sol + sim.solve() + assert MockSim.return_value.solve.call_count == 1 + + @pytest.mark.unit + def test_solution_data_has_expected_keys_power_mode(self, sim): + mock_sol = _mock_pybamm_sol(time_final=1.0) + with ( + patch.object(sim, "_compute_theoretical_value", return_value=50.0), + patch("pybamm.Experiment"), + patch("pybamm.Simulation") as MockSim, + ): + MockSim.return_value.solve.return_value = mock_sol + result = sim.solve() + assert "Power [W]" in result.data + assert "Energy [W.h]" in result.data + assert "Time [h]" in result.data + + @pytest.mark.unit + def test_current_convert_to_watts_adds_watt_keys(self, sim_current_watts): + mock_sol = _mock_pybamm_sol(time_final=1.0, energy_final=5.0) + with ( + patch.object( + sim_current_watts, "_compute_theoretical_value", return_value=50.0 + ), + patch("pybamm.Experiment"), + patch("pybamm.Simulation") as MockSim, + ): + MockSim.return_value.solve.return_value = mock_sol + result = sim_current_watts.solve() + assert "Power [W]" in result.data + assert "Energy [W.h]" in result.data diff --git a/tests/unit/test_solution.py b/tests/unit/test_solution.py new file mode 100644 index 0000000..8cfee87 --- /dev/null +++ b/tests/unit/test_solution.py @@ -0,0 +1,173 @@ +"""Unit tests for RagoneSolution.""" + +import numpy as np +import pytest +from unittest.mock import MagicMock, patch + +from ragone.solution import RagoneSolution + + +# --------------------------------------------------------------------------- +# Synthetic data for fit_log +# --------------------------------------------------------------------------- +# Exact match to the gaussian_log model with E0=1, P0=1, n=1. +# Starting from the default p0=[1,1,1], curve_fit converges immediately. +_P_FIT = np.array([0.1, 0.3, 0.5, 0.7, 1.0]) +_LOG_E_FIT = (1.0 - _P_FIT) / np.log(10) # gaussian_log(log10(P), 1, 1, 1) +_E_FIT = 10**_LOG_E_FIT + + +# --------------------------------------------------------------------------- +# __init__ +# --------------------------------------------------------------------------- + + +class TestRagoneSolutionInit: + @pytest.mark.unit + def test_power_mode_sets_input_label(self, power_solution): + assert power_solution.input == "Power [W]" + + @pytest.mark.unit + def test_power_mode_sets_output_label(self, power_solution): + assert power_solution.output == "Energy [W.h]" + + @pytest.mark.unit + def test_current_mode_sets_input_label(self, current_solution): + assert current_solution.input == "Current [A]" + + @pytest.mark.unit + def test_current_mode_sets_output_label(self, current_solution): + assert current_solution.output == "Capacity [A.h]" + + @pytest.mark.unit + def test_data_is_stored(self, power_data, power_solution): + assert power_solution.data is power_data + + @pytest.mark.unit + def test_mode_is_stored(self, power_solution): + assert power_solution.mode == "power" + + @pytest.mark.unit + def test_raw_metrics_initialised_to_none(self, power_solution): + assert power_solution._raw_metrics is None + + @pytest.mark.unit + def test_metrics_initialised_to_none(self, power_solution): + assert power_solution._metrics is None + + +# --------------------------------------------------------------------------- +# Private math functions +# --------------------------------------------------------------------------- + + +class TestRagoneSolutionMathFunctions: + @pytest.mark.unit + def test_gaussian_log_known_value(self, power_solution): + # x=0, E0=2, P0=1, n=1 → (2 - (10^0 / 1)^1) / ln(10) = 1/ln(10) + result = power_solution._gaussian_log(0.0, 2.0, 1.0, 1.0) + assert result == pytest.approx(1.0 / np.log(10)) + + @pytest.mark.unit + def test_gaussian_known_value(self, power_solution): + # x=2, E0=10, P0=2, n=1 → 10 * exp(-((2/2)^1)) = 10/e + result = power_solution._gaussian(2.0, 10.0, 2.0, 1.0) + assert result == pytest.approx(10.0 / np.e) + + @pytest.mark.unit + def test_gaussian_loglog_identical_to_gaussian_log(self, power_solution): + x = np.array([0.0, 0.5, 1.0]) + args = (2.0, 1.5, 2.0) + np.testing.assert_allclose( + power_solution._gaussian_loglog(x, *args), + power_solution._gaussian_log(x, *args), + ) + + @pytest.mark.unit + def test_gaussian_linear_identical_to_gaussian(self, power_solution): + x = np.array([1.0, 2.0, 5.0]) + args = (10.0, 3.0, 1.5) + np.testing.assert_allclose( + power_solution._gaussian_linear(x, *args), + power_solution._gaussian(x, *args), + ) + + +# --------------------------------------------------------------------------- +# fit_log +# --------------------------------------------------------------------------- + + +class TestRagoneSolutionFitLog: + @pytest.fixture + def fittable_solution(self): + data = { + "Power [W]": _P_FIT, + "Energy [W.h]": _E_FIT, + "Time [h]": _E_FIT / _P_FIT, + } + return RagoneSolution(data, "power") + + @pytest.mark.unit + def test_returns_array_of_three_params(self, fittable_solution): + popt = fittable_solution.fit_log() + assert len(popt) == 3 + + @pytest.mark.unit + def test_sets_raw_metrics(self, fittable_solution): + popt = fittable_solution.fit_log() + np.testing.assert_array_equal(fittable_solution._raw_metrics, popt) + + @pytest.mark.unit + def test_metrics_contains_n_key(self, fittable_solution): + fittable_solution.fit_log() + assert "n" in fittable_solution.metrics + + @pytest.mark.unit + def test_metrics_contains_energy_reference_key(self, fittable_solution): + fittable_solution.fit_log() + keys = list(fittable_solution.metrics) + assert any("energy" in k.lower() for k in keys) + + @pytest.mark.unit + def test_metrics_contains_power_reference_key(self, fittable_solution): + fittable_solution.fit_log() + keys = list(fittable_solution.metrics) + assert any("power" in k.lower() for k in keys) + + @pytest.mark.unit + def test_metrics_n_matches_popt(self, fittable_solution): + popt = fittable_solution.fit_log() + assert fittable_solution.metrics["n"] == pytest.approx(popt[2]) + + @pytest.mark.unit + def test_recovers_known_parameters(self, fittable_solution): + # Data was generated with E0=1, P0=1, n=1 — expect recovery + popt = fittable_solution.fit_log() + assert popt[0] == pytest.approx(1.0, rel=1e-3) + assert popt[1] == pytest.approx(1.0, rel=1e-3) + assert popt[2] == pytest.approx(1.0, rel=1e-3) + + +# --------------------------------------------------------------------------- +# plot() delegation +# --------------------------------------------------------------------------- + + +class TestRagoneSolutionPlot: + @pytest.mark.unit + def test_plot_delegates_to_ragone_plot(self, power_solution): + mock_fig, mock_ax = MagicMock(), MagicMock() + with patch("ragone.plotting.RagonePlot") as MockPlot: + MockPlot.return_value.plot.return_value = (mock_fig, mock_ax) + result = power_solution.plot() + assert result == (mock_fig, mock_ax) + + @pytest.mark.unit + def test_plot_passes_kwargs_to_ragone_plot(self, power_solution): + with patch("ragone.plotting.RagonePlot") as MockPlot: + MockPlot.return_value.plot.return_value = (MagicMock(), MagicMock()) + power_solution.plot(labels=["A"], volume=0.1, mass=0.2, scale="linear") + MockPlot.assert_called_once_with( + power_solution, labels=["A"], volume=0.1, mass=0.2, scale="linear" + )