Minor updates to plotting, dataset and interpolant

CHANGELOG.md

@@ -6,6 +6,7 @@
 
 ## Bug Fixes
 
+- [#915](https://github.com/pybop-team/PyBOP/pull/915) - Fixes axis labels for non-standard domain names, adds `Dataset` length property and adds `kind` property to `Interpolant`.
 - [#911](https://github.com/pybop-team/PyBOP/pull/911) - Fixes the passing of the cost log to the Voronoi surface plot.
 - [#905](https://github.com/pybop-team/PyBOP/pull/905) - Remove restriction on numpy.
 

examples/scripts/battery_parameterisation/gitt_fitting.py

@@ -35,7 +35,7 @@
 
 # Determine the indices corresponding to each pulse in the dataset
 nonzero_index = np.concatenate(
-    ([-1], np.flatnonzero(dataset["Current [A]"]), [len(dataset["Current [A]"]) + 1])
+    ([-1], np.flatnonzero(dataset["Current [A]"]), [len(dataset) + 1])
 )
 pulse_starts = np.extract(
     nonzero_index[1:] - nonzero_index[:-1] != 1,  # check if there is a gap

pybop/models/lithium_ion/utils.py

@@ -29,6 +29,8 @@ class Interpolant:
         Output values corresponding to x.
     name : str, optional
         Name for the interpolant when used in PyBaMM.
+    kind: str, optional
+        Which kind of interpolator to use. Can be "linear" (default) or "cubic".
     bounds_error : bool, optional
         If True, raise error when interpolating outside bounds.
     fill_value : str or float, optional
@@ -42,13 +44,15 @@ def __init__(
         x: np.ndarray,
         y: np.ndarray,
         name: str | None = None,
+        kind: str | None = None,
         bounds_error: bool = False,
         fill_value: str | float = "extrapolate",
         axis: int = 0,
     ):
         self.x = np.asarray(x)
         self.y = np.asarray(y)
         self.name = name
+        self.kind = kind or "linear"
         self._interp_func = self._create_interpolant(bounds_error, fill_value, axis)
 
     def _create_interpolant(
@@ -58,6 +62,7 @@ def _create_interpolant(
         return interpolate.interp1d(
             self.x,
             self.y,
+            kind=self.kind,
             bounds_error=bounds_error,
             fill_value=fill_value,
             axis=axis,
@@ -82,7 +87,9 @@ def __call__(self, x: float | np.ndarray):
             return self._interp_func(x)
         except Exception:
             # Fall back to PyBaMM interpolant for symbolic evaluation
-            return PybammInterpolant(self.x, self.y, x, name=self.name)
+            return PybammInterpolant(
+                self.x, self.y, x, name=self.name, interpolator=self.kind
+            )
 
 
 class InverseOCV:

pybop/plot/dataset.py

@@ -34,7 +34,7 @@ def dataset(dataset, signal=None, trace_names=None, show=True, **layout_kwargs):
     # Compile ydata and labels or legend
     y = [dataset[s] for s in signal]
     if len(signal) == 1:
-        yaxis_title = signal[0]
+        yaxis_title = StandardPlot.remove_brackets(signal[0])
         if trace_names is None:
             trace_names = ["Data"]
     else:

pybop/plot/problem.py

@@ -73,7 +73,7 @@ def problem(
         plot_dict = StandardPlot(
             layout_options=dict(
                 title="Scatter Plot",
-                xaxis_title="Time / s",
+                xaxis_title=StandardPlot.remove_brackets(domain),
                 yaxis_title=StandardPlot.remove_brackets(var),
             )
         )

pybop/processing/dataset.py

@@ -66,6 +66,10 @@ def __getitem__(self, key):
 
         return self.data[key]
 
+    def __len__(self) -> int:
+        """Return the length of the data, based on the length of the domain data."""
+        return len(self.data[self.domain])
+
     def check(self, domain: str = None, signal: str | list[str] = None) -> bool:
         """
         Check the consistency of a PyBOP Dataset against the expected format.

pybop/simulators/solution.py

@@ -21,7 +21,7 @@ class Solution:
     """
 
     def __init__(self, inputs: Inputs = None):
-        self._dict = {}
+        self._variables = {}
         self.all_inputs = [inputs] if inputs is not None else []
 
     def set_solution_variable(
@@ -30,9 +30,9 @@ def set_solution_variable(
         data: np.ndarray,
         sensitivities: dict[str, np.ndarray] | None = None,
     ):
-        self._dict[variable_name] = SolutionVariable(
+        self._variables[variable_name] = SolutionVariable(
             data=data, sensitivities=sensitivities
         )
 
     def __getitem__(self, key):
-        return self._dict[key]
+        return self._variables[key]

tests/unit/test_dataset.py

@@ -63,7 +63,7 @@ def test_dataset(self):
 
         # Test get subset
         dataset = dataset.get_subset(list(range(5)))
-        assert len(dataset[dataset.domain]) == 5
+        assert len(dataset) == 5
 
         # Form frequency dataset
         data_dictionary = {
@@ -259,7 +259,7 @@ def dataset(self):
     def test_current_data_processing(self, dataset):
         # Test generation of a current consistent with the charge throughput data
         consistent_dataset = pybop.generate_consistent_current(dataset, tolerance=1e-2)
-        assert len(consistent_dataset["Time [s]"]) >= len(dataset["Time [s]"])
+        assert len(consistent_dataset) >= len(dataset)
 
         for var in ["Time [s]", "Current [A]", "Discharge capacity [A.h]"]:
             assert consistent_dataset[var][0] == dataset[var][0]
@@ -275,7 +275,7 @@ def test_current_data_processing(self, dataset):
 
         # Test downsampling of constant current sections
         downsampled_dataset = pybop.downsample_constant_current(dataset, tolerance=1e-4)
-        assert len(downsampled_dataset["Time [s]"]) < len(dataset["Time [s]"])
+        assert len(downsampled_dataset) < len(dataset)
 
         for var in ["Time [s]", "Current [A]", "Discharge capacity [A.h]"]:
             assert downsampled_dataset[var][0] == dataset[var][0]
@@ -302,7 +302,7 @@ def test_current_data_processing(self, dataset):
             }
         )
         ds_dataset = pybop.downsample_constant_current(dataset_wo_ct, tolerance=1e-4)
-        assert len(ds_dataset["Time [s]"]) < len(dataset["Time [s]"])
+        assert len(ds_dataset) < len(dataset)
 
         for var in ["Time [s]", "Current [A]"]:
             assert ds_dataset[var][0] == dataset_wo_ct[var][0]

tests/unit/test_problem.py

@@ -106,7 +106,7 @@ def test_fitting_problem(self, simulator, dataset):
         assert_array_equal(target_data, dataset["Voltage [V]"])
 
         # Test set target
-        dataset["Voltage [V]"] += np.random.normal(0, 0.05, len(dataset["Voltage [V]"]))
+        dataset["Voltage [V]"] += np.random.normal(0, 0.05, len(dataset))
         cost.set_target("Voltage [V]", dataset)
         problem = pybop.Problem(simulator, cost)