Merge pull request pybamm-team#1678 from Saransh-cpp/plot-summary-var…

…iables

Added a function to plot "summary variables"

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 ## Features
 
+-   Added `plot_summary_variables` to plot and compare summary variables ([#1678](https://github.com/pybamm-team/PyBaMM/pull/1678))
 -   The DFN model can now be used directly (instead of `BasicDFNHalfCell`) to simulate a half-cell ([#1600](https://github.com/pybamm-team/PyBaMM/pull/1600))
 
 ## Breaking changes

docs/source/plotting/index.rst

@@ -8,3 +8,4 @@ Plotting
   plot
   plot_2D
   plot_voltage_components
+  plot_summary_variables

docs/source/plotting/plot_summary_variables.rst

@@ -0,0 +1,4 @@
+Plot Summary Variables
+======================
+
+.. autofunction:: pybamm.plot_summary_variables

pybamm/__init__.py

@@ -249,6 +249,7 @@ def version(formatted=False):
 from .plotting.plot import plot
 from .plotting.plot2D import plot2D
 from .plotting.plot_voltage_components import plot_voltage_components
+from .plotting.plot_summary_variables import plot_summary_variables
 from .plotting.dynamic_plot import dynamic_plot
 
 #

pybamm/plotting/plot_summary_variables.py

@@ -0,0 +1,79 @@
+#
+# Method for plotting/comparing summary variables
+#
+import numpy as np
+import pybamm
+
+
+def plot_summary_variables(
+    solutions, output_variables=None, labels=None, testing=False, **kwargs_fig
+):
+    """
+    Generate a plot showing/comparing the summary variables.
+
+    Parameters
+    ----------
+    solutions : (iter of) :class:`pybamm.Solution`
+        The solution(s) for the model(s) from which to extract summary variables.
+    output_variables: list (optional)
+        A list of variables to plot automatically. If None, the default ones are used.
+    labels: list (optional)
+        A list of labels to be added to the legend. No labels are added by default.
+    testing : bool (optional)
+        Whether to actually make the plot (turned off for unit tests).
+    kwargs_fig
+        Keyword arguments, passed to plt.subplots.
+
+    """
+    import matplotlib.pyplot as plt
+
+    if isinstance(solutions, pybamm.Solution):
+        solutions = [solutions]
+
+    # setting a default value for figsize
+    kwargs_fig = {"figsize": (15, 8), **kwargs_fig}
+
+    if output_variables is None:
+        output_variables = [
+            "Capacity [A.h]",
+            "Loss of lithium inventory [%]",
+            "Loss of capacity to SEI [A.h]",
+            "Loss of active material in negative electrode [%]",
+            "Loss of active material in positive electrode [%]",
+            "x_100",
+            "x_0",
+            "y_100",
+            "y_0",
+        ]
+
+    # find the number of subplots to be created
+    length = len(output_variables)
+    n = int(length // np.sqrt(length))
+    m = int(np.ceil(length / n))
+
+    # create subplots
+    fig, axes = plt.subplots(n, m, **kwargs_fig)
+
+    # loop through the subplots and plot the output_variables
+    for var, ax in zip(output_variables, axes.flat):
+        # loop through the solutions to compare output_variables
+        for solution in solutions:
+            # plot summary variable v/s cycle number
+            ax.plot(
+                solution.summary_variables["Cycle number"],
+                solution.summary_variables[var],
+            )
+        # label the axes
+        ax.set_xlabel("Cycle number")
+        ax.set_ylabel(var)
+        ax.set_xlim([1, solution.summary_variables["Cycle number"][-1]])
+
+    fig.tight_layout()
+
+    # add labels in legend
+    if labels is not None:  # pragma: no cover
+        fig.legend(labels, loc="lower right")
+    if not testing:  # pragma: no cover
+        plt.show()
+
+    return axes

tests/unit/test_plotting/test_plot_summary_variables.py

@@ -0,0 +1,86 @@
+import pybamm
+import unittest
+import numpy as np
+
+
+class TestPlotSummaryVariables(unittest.TestCase):
+    def test_plot(self):
+        model = pybamm.lithium_ion.SPM({"SEI": "ec reaction limited"})
+        parameter_values = pybamm.ParameterValues(
+            chemistry=pybamm.parameter_sets.Mohtat2020
+        )
+        experiment = pybamm.Experiment(
+            [
+                (
+                    "Discharge at C/10 for 10 hours or until 3.3 V",
+                    "Rest for 1 hour",
+                    "Charge at 1 A until 4.1 V",
+                    "Hold at 4.1 V until 50 mA",
+                    "Rest for 1 hour",
+                )
+            ]
+            * 3,
+        )
+        output_variables = [
+            "Capacity [A.h]",
+            "Loss of lithium inventory [%]",
+            "Loss of capacity to SEI [A.h]",
+            "Loss of active material in negative electrode [%]",
+            "Loss of active material in positive electrode [%]",
+            "x_100",
+            "x_0",
+            "y_100",
+            "y_0",
+        ]
+        sim = pybamm.Simulation(
+            model, experiment=experiment, parameter_values=parameter_values
+        )
+        sol = sim.solve(initial_soc=1)
+
+        axes = pybamm.plot_summary_variables(sol, testing=True)
+
+        axes = axes.flatten()
+        self.assertEqual(len(axes), 9)
+
+        for output_var, ax in zip(output_variables, axes):
+            self.assertEqual(ax.get_xlabel(), "Cycle number")
+            self.assertEqual(ax.get_ylabel(), output_var)
+
+            cycle_number, var = ax.get_lines()[0].get_data()
+            np.testing.assert_array_equal(
+                cycle_number, sol.summary_variables["Cycle number"]
+            )
+            np.testing.assert_array_equal(var, sol.summary_variables[output_var])
+
+        axes = pybamm.plot_summary_variables(
+            [sol, sol], labels=["SPM", "SPM"], testing=True
+        )
+
+        axes = axes.flatten()
+        self.assertEqual(len(axes), 9)
+
+        for output_var, ax in zip(output_variables, axes):
+            self.assertEqual(ax.get_xlabel(), "Cycle number")
+            self.assertEqual(ax.get_ylabel(), output_var)
+
+            cycle_number, var = ax.get_lines()[0].get_data()
+            np.testing.assert_array_equal(
+                cycle_number, sol.summary_variables["Cycle number"]
+            )
+            np.testing.assert_array_equal(var, sol.summary_variables[output_var])
+
+            cycle_number, var = ax.get_lines()[1].get_data()
+            np.testing.assert_array_equal(
+                cycle_number, sol.summary_variables["Cycle number"]
+            )
+            np.testing.assert_array_equal(var, sol.summary_variables[output_var])
+
+
+if __name__ == "__main__":
+    print("Add -v for more debug output")
+    import sys
+
+    if "-v" in sys.argv:
+        debug = True
+    pybamm.settings.debug_mode = True
+    unittest.main()