Rename plot.quick to plot.problem (#684)

NicolaCourtier · web-flow · commit 7e4d250a4cec · 2025-03-28T14:21:46.000Z
* Rename plot.quick to plot.problem

* Update CHANGELOG.md

* Update missed examples

* Align new examples
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -19,6 +19,7 @@
 
 ## Breaking Changes
 
+- [#684](https://github.com/pybop-team/PyBOP/pull/684) - Updates `plot.quick` to `plot.problem` for clarity.
 - [#661](https://github.com/pybop-team/PyBOP/pull/661) - Adds `pybop.CostInterface` which aligns the optimisers and samplers with a unified `call_cost` in which transformations and sign inversions are applied. Also includes bug fixes for transformations and gradient calculations.
 
 
diff --git a/examples/notebooks/battery_parameterisation/ecm_trust-constr.ipynb b/examples/notebooks/battery_parameterisation/ecm_trust-constr.ipynb
@@ -415,7 +415,7 @@
     "pybop.plot.dataset(dataset)\n",
     "\n",
     "# Plot the timeseries output\n",
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\")\n",
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\")\n",
     "\n",
     "# Plot convergence\n",
     "pybop.plot.convergence(optim)\n",
diff --git a/examples/notebooks/battery_parameterisation/electrode_balancing.ipynb b/examples/notebooks/battery_parameterisation/electrode_balancing.ipynb
@@ -313,7 +313,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
diff --git a/examples/notebooks/battery_parameterisation/equivalent_circuit_identification.ipynb b/examples/notebooks/battery_parameterisation/equivalent_circuit_identification.ipynb
@@ -425,7 +425,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
diff --git a/examples/notebooks/battery_parameterisation/equivalent_circuit_identification_hppc.ipynb b/examples/notebooks/battery_parameterisation/equivalent_circuit_identification_hppc.ipynb
@@ -342,7 +342,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
diff --git a/examples/notebooks/battery_parameterisation/equivalent_circuit_identification_multipulse.ipynb b/examples/notebooks/battery_parameterisation/equivalent_circuit_identification_multipulse.ipynb
@@ -469,7 +469,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
diff --git a/examples/notebooks/battery_parameterisation/monte_carlo_ecm_identification.ipynb b/examples/notebooks/battery_parameterisation/monte_carlo_ecm_identification.ipynb
@@ -548,7 +548,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, results_optim.x)\n",
+    "pybop.plot.problem(problem, results_optim.x)\n",
     "pybop.plot.convergence(optim)\n",
     "pybop.plot.parameters(optim);"
    ]
@@ -921,7 +921,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, posterior_summary.mean);"
+    "pybop.plot.problem(problem, posterior_summary.mean);"
    ]
   },
   {
diff --git a/examples/notebooks/battery_parameterisation/multi_model_identification.ipynb b/examples/notebooks/battery_parameterisation/multi_model_identification.ipynb
@@ -546,7 +546,7 @@
    ],
    "source": [
     "for optim, x in zip(optims, xs):\n",
-    "    pybop.plot.quick(\n",
+    "    pybop.plot.problem(\n",
     "        optim.cost.problem, problem_inputs=x, title=optim.cost.problem.model.name\n",
     "    )"
    ]
diff --git a/examples/notebooks/battery_parameterisation/pouch_cell_identification.ipynb b/examples/notebooks/battery_parameterisation/pouch_cell_identification.ipynb
@@ -469,7 +469,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
diff --git a/examples/notebooks/battery_parameterisation/single_pulse_circuit_model.ipynb b/examples/notebooks/battery_parameterisation/single_pulse_circuit_model.ipynb
@@ -494,7 +494,7 @@
    "source": [
     "## Plotting and Visualisation\n",
     "\n",
-    "PyBOP provides various plotting utilities to visualise the results of the optimisation. The `pybop.plot.quick` method provides a fast scatter of two variables. For this example, we plot the identified parameter set to the target dataset. The default plot is voltage vs time as shown below."
+    "PyBOP provides various plotting utilities to visualise the results of the optimisation. The `pybop.plot.problem` method provides a fast scatter of two variables. For this example, we plot the identified parameter set to the target dataset. The default plot is voltage vs time as shown below."
    ]
   },
   {
@@ -538,7 +538,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
@@ -747,7 +747,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Parameter Extrapolation\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Parameter Extrapolation\");"
    ]
   },
   {
diff --git a/examples/notebooks/comparison_examples/multi_optimiser_identification.ipynb b/examples/notebooks/comparison_examples/multi_optimiser_identification.ipynb
@@ -1002,7 +1002,7 @@
    ],
    "source": [
     "for optim, x in zip(optims, xs):\n",
-    "    pybop.plot.quick(optim.cost.problem, problem_inputs=x, title=optim.name())"
+    "    pybop.plot.problem(optim.cost.problem, problem_inputs=x, title=optim.name())"
    ]
   },
   {
diff --git a/examples/notebooks/comparison_examples/optimiser_calibration.ipynb b/examples/notebooks/comparison_examples/optimiser_calibration.ipynb
@@ -421,7 +421,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
@@ -1519,7 +1519,7 @@
    "source": [
     "optim = pybop.Optimisation(cost, optimiser=pybop.GradientDescent, sigma0=0.08)\n",
     "results = optim.run()\n",
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
diff --git a/examples/notebooks/design_optimisation/energy_based_electrode_design.ipynb b/examples/notebooks/design_optimisation/energy_based_electrode_design.ipynb
@@ -389,7 +389,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
diff --git a/examples/notebooks/getting_started/adamw_identification.ipynb b/examples/notebooks/getting_started/adamw_identification.ipynb
@@ -449,7 +449,7 @@
     }
    ],
    "source": [
-    "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
+    "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"
    ]
   },
   {
diff --git a/examples/scripts/battery_parameterisation/ecm_tau_constraints.py b/examples/scripts/battery_parameterisation/ecm_tau_constraints.py
@@ -172,7 +172,7 @@ def check_params(
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/battery_parameterisation/full_cell_balancing.py b/examples/scripts/battery_parameterisation/full_cell_balancing.py
@@ -83,7 +83,7 @@ def noisy(data, sigma):
 print("True parameters:", parameters.true_value())
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/battery_parameterisation/gitt_weppner_huggins.py b/examples/scripts/battery_parameterisation/gitt_weppner_huggins.py
@@ -58,7 +58,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/battery_parameterisation/simple_ecm.py b/examples/scripts/battery_parameterisation/simple_ecm.py
@@ -87,7 +87,7 @@
 pybop.plot.dataset(dataset)
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/battery_parameterisation/simple_pulse_fit.py b/examples/scripts/battery_parameterisation/simple_pulse_fit.py
@@ -79,7 +79,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/battery_parameterisation/tau_reparameterised_ecm.py b/examples/scripts/battery_parameterisation/tau_reparameterised_ecm.py
@@ -115,7 +115,7 @@
 print("Estimated parameters:", results.x.tolist() + [results.x[2] / results.x[1]])
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/adamw.py b/examples/scripts/comparison_examples/adamw.py
@@ -77,7 +77,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/covariance_matrix_adaptation.py b/examples/scripts/comparison_examples/covariance_matrix_adaptation.py
@@ -61,7 +61,7 @@
 pybop.plot.dataset(dataset)
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x_best, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x_best, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/cuckoo.py b/examples/scripts/comparison_examples/cuckoo.py
@@ -66,7 +66,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/exponential_decay.py b/examples/scripts/comparison_examples/exponential_decay.py
@@ -59,7 +59,7 @@ def noisy(data, sigma):
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/exponential_natural_evolution.py b/examples/scripts/comparison_examples/exponential_natural_evolution.py
@@ -42,7 +42,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/gradient_descent.py b/examples/scripts/comparison_examples/gradient_descent.py
@@ -49,7 +49,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/irpropmin.py b/examples/scripts/comparison_examples/irpropmin.py
@@ -63,7 +63,7 @@
 print(parameters.true_value())
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/maximum_a_posteriori.py b/examples/scripts/comparison_examples/maximum_a_posteriori.py
@@ -77,7 +77,7 @@
 print("True parameters:", parameters.true_value())
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/maximum_likelihood.py b/examples/scripts/comparison_examples/maximum_likelihood.py
@@ -68,7 +68,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/nelder_mead.py b/examples/scripts/comparison_examples/nelder_mead.py
@@ -71,7 +71,7 @@ def noisy(data, sigma):
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/particle_swarm.py b/examples/scripts/comparison_examples/particle_swarm.py
@@ -48,7 +48,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/random_search.py b/examples/scripts/comparison_examples/random_search.py
@@ -61,7 +61,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/scipy_minimize.py b/examples/scripts/comparison_examples/scipy_minimize.py
@@ -50,7 +50,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/simulated_annealing.py b/examples/scripts/comparison_examples/simulated_annealing.py
@@ -55,7 +55,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/stochastic_natural_evolution.py b/examples/scripts/comparison_examples/stochastic_natural_evolution.py
@@ -41,7 +41,7 @@
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/comparison_examples/unscented_kalman_filter.py b/examples/scripts/comparison_examples/unscented_kalman_filter.py
@@ -63,7 +63,7 @@
 results = optim.run()
 
 # Plot the timeseries output (requires model that returns Voltage)
-pybop.plot.quick(observer, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(observer, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/design_optimisation/maximising_energy.py b/examples/scripts/design_optimisation/maximising_energy.py
@@ -84,7 +84,7 @@
 print(f"Optimised volumetric energy density: {cost2(results.x):.2f} Wh.m-3")
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot the cost landscape with optimisation path
 pybop.plot.surface(optim)
diff --git a/examples/scripts/design_optimisation/maximising_power.py b/examples/scripts/design_optimisation/maximising_power.py
@@ -79,7 +79,7 @@
 )
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot the cost landscape with optimisation path
 pybop.plot.surface(optim)
diff --git a/examples/scripts/getting_started/ask-tell-interface.py b/examples/scripts/getting_started/ask-tell-interface.py
@@ -82,6 +82,6 @@
         )
 
 # Plot the timeseries output
-pybop.plot.quick(
+pybop.plot.problem(
     problem, problem_inputs=optim.optimiser.x_best(), title="Optimised Comparison"
 )
diff --git a/examples/scripts/getting_started/functional_parameters.py b/examples/scripts/getting_started/functional_parameters.py
@@ -84,7 +84,7 @@ def positive_electrode_exchange_current_density(c_e, c_s_surf, c_s_max, T):
 results = optim.run()
 
 # Plot the timeseries output
-pybop.plot.quick(problem, problem_inputs=results.x, title="Optimised Comparison")
+pybop.plot.problem(problem, problem_inputs=results.x, title="Optimised Comparison")
 
 # Plot convergence
 pybop.plot.convergence(optim)
diff --git a/examples/scripts/getting_started/linked_parameters.py b/examples/scripts/getting_started/linked_parameters.py
diff --git a/examples/scripts/getting_started/multi_fitting.py b/examples/scripts/getting_started/multi_fitting.py
diff --git a/examples/scripts/getting_started/multi_start_optimisation.py b/examples/scripts/getting_started/multi_start_optimisation.py
diff --git a/examples/scripts/getting_started/simple_BPX.py b/examples/scripts/getting_started/simple_BPX.py
diff --git a/examples/scripts/getting_started/simple_dfn.py b/examples/scripts/getting_started/simple_dfn.py
diff --git a/examples/scripts/getting_started/weighted_cost.py b/examples/scripts/getting_started/weighted_cost.py
diff --git a/pybop/plot/__init__.py b/pybop/plot/__init__.py
diff --git a/pybop/plot/problem.py b/pybop/plot/problem.py
diff --git a/tests/unit/test_plots.py b/tests/unit/test_plots.py

Original file line number	Diff line number	Diff line change
`@@ -19,6 +19,7 @@`
`19`	`19`
`20`	`20`	`## Breaking Changes`
`21`	`21`
	`22`	+- [#684](https://github.com/pybop-team/PyBOP/pull/684) - Updates `plot.quick` to `plot.problem` for clarity.
`22`	`23`	- [#661](https://github.com/pybop-team/PyBOP/pull/661) - Adds `pybop.CostInterface` which aligns the optimisers and samplers with a unified `call_cost` in which transformations and sign inversions are applied. Also includes bug fixes for transformations and gradient calculations.
`23`	`24`
`24`	`25`
Original file line number	Diff line number	Diff line change
`@@ -313,7 +313,7 @@`
`313`	`313`	`}`
`314`	`314`	`],`
`315`	`315`	`"source": [`
`316`		`- "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
	`316`	`+ "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
`317`	`317`	`]`
`318`	`318`	`},`
`319`	`319`	`{`
Original file line number	Diff line number	Diff line change
`@@ -425,7 +425,7 @@`
`425`	`425`	`}`
`426`	`426`	`],`
`427`	`427`	`"source": [`
`428`		`- "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
	`428`	`+ "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
`429`	`429`	`]`
`430`	`430`	`},`
`431`	`431`	`{`
Original file line number	Diff line number	Diff line change
`@@ -342,7 +342,7 @@`
`342`	`342`	`}`
`343`	`343`	`],`
`344`	`344`	`"source": [`
`345`		`- "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
	`345`	`+ "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
`346`	`346`	`]`
`347`	`347`	`},`
`348`	`348`	`{`
Original file line number	Diff line number	Diff line change
`@@ -469,7 +469,7 @@`
`469`	`469`	`}`
`470`	`470`	`],`
`471`	`471`	`"source": [`
`472`		`- "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
	`472`	`+ "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
`473`	`473`	`]`
`474`	`474`	`},`
`475`	`475`	`{`
Original file line number	Diff line number	Diff line change
`@@ -548,7 +548,7 @@`
`548`	`548`	`}`
`549`	`549`	`],`
`550`	`550`	`"source": [`
`551`		`- "pybop.plot.quick(problem, results_optim.x)\n",`
	`551`	`+ "pybop.plot.problem(problem, results_optim.x)\n",`
`552`	`552`	`"pybop.plot.convergence(optim)\n",`
`553`	`553`	`"pybop.plot.parameters(optim);"`
`554`	`554`	`]`
`@@ -921,7 +921,7 @@`
`921`	`921`	`}`
`922`	`922`	`],`
`923`	`923`	`"source": [`
`924`		`- "pybop.plot.quick(problem, posterior_summary.mean);"`
	`924`	`+ "pybop.plot.problem(problem, posterior_summary.mean);"`
`925`	`925`	`]`
`926`	`926`	`},`
`927`	`927`	`{`
Original file line number	Diff line number	Diff line change
`@@ -546,7 +546,7 @@`
`546`	`546`	`],`
`547`	`547`	`"source": [`
`548`	`548`	`"for optim, x in zip(optims, xs):\n",`
`549`		`- " pybop.plot.quick(\n",`
	`549`	`+ " pybop.plot.problem(\n",`
`550`	`550`	`" optim.cost.problem, problem_inputs=x, title=optim.cost.problem.model.name\n",`
`551`	`551`	`" )"`
`552`	`552`	`]`
Original file line number	Diff line number	Diff line change
`@@ -494,7 +494,7 @@`
`494`	`494`	`"source": [`
`495`	`495`	`"## Plotting and Visualisation\n",`
`496`	`496`	`"\n",`
`497`		- "PyBOP provides various plotting utilities to visualise the results of the optimisation. The `pybop.plot.quick` method provides a fast scatter of two variables. For this example, we plot the identified parameter set to the target dataset. The default plot is voltage vs time as shown below."
	`497`	+ "PyBOP provides various plotting utilities to visualise the results of the optimisation. The `pybop.plot.problem` method provides a fast scatter of two variables. For this example, we plot the identified parameter set to the target dataset. The default plot is voltage vs time as shown below."
`498`	`498`	`]`
`499`	`499`	`},`
`500`	`500`	`{`
`@@ -538,7 +538,7 @@`
`538`	`538`	`}`
`539`	`539`	`],`
`540`	`540`	`"source": [`
`541`		`- "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
	`541`	`+ "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Optimised Comparison\");"`
`542`	`542`	`]`
`543`	`543`	`},`
`544`	`544`	`{`
`@@ -747,7 +747,7 @@`
`747`	`747`	`}`
`748`	`748`	`],`
`749`	`749`	`"source": [`
`750`		`- "pybop.plot.quick(problem, problem_inputs=results.x, title=\"Parameter Extrapolation\");"`
	`750`	`+ "pybop.plot.problem(problem, problem_inputs=results.x, title=\"Parameter Extrapolation\");"`
`751`	`751`	`]`
`752`	`752`	`},`
`753`	`753`	`{`