from pybop.parameters.parameter import Inputs
from pybop.plot.standard_plots import StandardPlot
[docs]
def nyquist(problem, problem_inputs: Inputs = None, show=True, **layout_kwargs):
"""
Generates Nyquist plots for the given problem by evaluating the model's output and target values.
Parameters
----------
problem : pybop.Problem
An instance of a problem class that contains the parameters and methods
for evaluation and target retrieval.
problem_inputs : Inputs, optional
Input parameters for the problem. If not provided, the default parameters from the problem
instance will be used. These parameters are verified before use (default is None).
show : bool, optional
If True, the plots will be displayed.
**layout_kwargs : dict, optional
Additional keyword arguments for customising the plot layout. These arguments are passed to
`fig.update_layout()`.
Returns
-------
list
A list of plotly `Figure` objects, each representing a Nyquist plot for the model's output and target values.
Notes
-----
- The function extracts the real part of the impedance from the model's output and the real and imaginary parts
of the impedance from the target output.
- For each signal in the problem, a Nyquist plot is created with the model's impedance plotted as a scatter plot.
- An additional trace for the reference (target output) is added to the plot.
- The plot layout can be customised using `layout_kwargs`.
Example
-------
>>> problem = pybop.EISProblem()
>>> nyquist_figures = nyquist(problem, show=True, title="Nyquist Plot", xaxis_title="Real(Z)", yaxis_title="Imag(Z)")
>>> # The plots will be displayed and nyquist_figures will contain the list of figure objects.
"""
if not isinstance(problem_inputs, dict):
problem_inputs = problem.parameters.to_dict(problem_inputs)
model_output = problem.simulate(problem_inputs)
domain_data = model_output["Impedance"].real
target_output = problem.target_data
figure_list = []
for var in problem.target:
default_layout_options = dict(
title="Nyquist Plot",
font=dict(family="Arial", size=14),
plot_bgcolor="white",
paper_bgcolor="white",
xaxis=dict(
title=dict(text="Z<sub>re</sub> / Ω", font=dict(size=16), standoff=15),
showline=True,
linewidth=2,
linecolor="black",
mirror=True,
ticks="outside",
tickwidth=2,
tickcolor="black",
ticklen=5,
),
yaxis=dict(
title=dict(text="-Z<sub>im</sub> / Ω", font=dict(size=16), standoff=15),
showline=True,
linewidth=2,
linecolor="black",
mirror=True,
ticks="outside",
tickwidth=2,
tickcolor="black",
ticklen=5,
scaleanchor="x",
scaleratio=1,
),
legend=dict(
x=0.02,
y=0.98,
bgcolor="rgba(255, 255, 255, 0.5)",
bordercolor="black",
borderwidth=1,
),
width=600,
height=600,
)
plot_dict = StandardPlot(
x=domain_data,
y=-model_output[var].imag,
layout_options=default_layout_options,
trace_names="Model",
)
plot_dict.traces[0].update(
mode="lines+markers",
line=dict(color="blue", width=2),
marker=dict(size=8, color="blue", symbol="circle"),
)
target_trace = plot_dict.create_trace(
x=target_output[var].real,
y=-target_output[var].imag,
name="Reference",
mode="markers",
marker=dict(size=8, color="red", symbol="circle-open"),
showlegend=True,
)
plot_dict.traces.append(target_trace)
fig = plot_dict(show=False)
# Add minor gridlines
fig.update_xaxes(
showgrid=True,
gridwidth=1,
gridcolor="lightgray",
minor=dict(showgrid=True, gridwidth=0.5, gridcolor="lightgray"),
)
fig.update_yaxes(
showgrid=True,
gridwidth=1,
gridcolor="lightgray",
minor=dict(showgrid=True, gridwidth=0.5, gridcolor="lightgray"),
)
# Overwrite with user-kwargs
fig.update_layout(**layout_kwargs)
if show:
fig.show()
figure_list.append(fig)
return figure_list