Make get_spatial_var private (pybamm-team#3755)

* Make `get_spatial_var` private `quick_plot.py`

* Remove round brackets around optional keyword in `QuickPlot.create_gif`

* Make Args in `dynamic_plot` optional

* Document dynamic arg in `pybamm.QuickPlot.plot`

* Add `get_spatial_var` info in `breaking changes` inside `CHANGELOG.md`

---------

Co-authored-by: Robert Timms <[email protected]>
Co-authored-by: Eric G. Kratz <[email protected]>

CHANGELOG.md

@@ -82,6 +82,7 @@
 
 ## Breaking changes
 
+- The function `get_spatial_var` in `pybamm.QuickPlot.py` is made private. ([#3755](https://github.com/pybamm-team/PyBaMM/pull/3755))
 - The parameters `GeometricParameters.A_cooling` and `GeometricParameters.V_cell` are now automatically computed from the electrode heights, widths and thicknesses if the "cell geometry" option is "pouch" and from the parameters "Cell cooling surface area [m2]" and "Cell volume [m3]", respectively, otherwise. When using the lumped thermal model we recommend using the "arbitrary" cell geometry and specifying the parameters "Cell cooling surface area [m2]", "Cell volume [m3]" and "Total heat transfer coefficient [W.m-2.K-1]" directly. ([#3707](https://github.com/pybamm-team/PyBaMM/pull/3707))
 - Dropped support for the `[jax]` extra, i.e., the Jax solver when running on Python 3.8. The Jax solver is now available on Python 3.9 and above ([#3550](https://github.com/pybamm-team/PyBaMM/pull/3550))
 

pybamm/plotting/quick_plot.py

@@ -301,7 +301,7 @@ def set_output_variables(self, output_variables, solutions):
 
             # Set the x variable (i.e. "x" or "r" for any one-dimensional variables)
             if first_variable.dimensions == 1:
-                (spatial_var_name, spatial_var_value) = self.get_spatial_var(
+                (spatial_var_name, spatial_var_value) = self._get_spatial_var(
                     variable_tuple, first_variable, "first"
                 )
                 self.spatial_variable_dict[variable_tuple] = {
@@ -324,11 +324,11 @@ def set_output_variables(self, output_variables, solutions):
                     (
                         first_spatial_var_name,
                         first_spatial_var_value,
-                    ) = self.get_spatial_var(variable_tuple, first_variable, "first")
+                    ) = self._get_spatial_var(variable_tuple, first_variable, "first")
                     (
                         second_spatial_var_name,
                         second_spatial_var_value,
-                    ) = self.get_spatial_var(variable_tuple, first_variable, "second")
+                    ) = self._get_spatial_var(variable_tuple, first_variable, "second")
                     self.spatial_variable_dict[variable_tuple] = {
                         first_spatial_var_name: first_spatial_var_value,
                         second_spatial_var_name: second_spatial_var_value,
@@ -360,7 +360,7 @@ def set_output_variables(self, output_variables, solutions):
             self.variables[variable_tuple] = variables
             self.subplot_positions[variable_tuple] = (self.n_rows, self.n_cols, k + 1)
 
-    def get_spatial_var(self, key, variable, dimension):
+    def _get_spatial_var(self, key, variable, dimension):
         """Return the appropriate spatial variable(s)"""
 
         # Extract name and value
@@ -465,8 +465,8 @@ def plot(self, t, dynamic=False):
         t : float
             Dimensional time (in 'time_units') at which to plot.
         dynamic : bool, optional
+            Determine whether to allocate space for a slider at the bottom of the plot when generating a dynamic plot.
             If True, creates a dynamic plot with a slider.
-
         """
 
         plt = import_optional_dependency("matplotlib.pyplot")