Circuits

class impedance.circuits.BaseCircuit(initial_guess, name=None, bounds=None)

Base class for equivalent circuit models

Methods

fit(self, frequencies, impedance[, method, …])	Fit the circuit model
get_param_names(self)	Converts circuit string to names
get_verbose_string(self)	Defines the pretty printing of all data in the circuit
plot(self[, ax, f_data, Z_data, …])	a convenience method for plotting Nyquist plots
predict(self, frequencies[, use_initial])	Predict impedance using a fit equivalent circuit model

fit(self, frequencies, impedance, method='lm', bounds=None)

Fit the circuit model

Parameters:

frequencies: numpy array

Frequencies

impedance: numpy array of dtype ‘complex128’

Impedance values to fit

method: {‘lm’, ‘trf’, ‘dogbox’}, optional

Name of method to pass to scipy.optimize.curve_fit

bounds: 2-tuple of array_like, optional

Lower and upper bounds on parameters. Defaults to bounds on all parameters of 0 and np.inf, except the CPE alpha which has an upper bound of 1

Returns:

self: returns an instance of self

get_param_names(self)

Converts circuit string to names

get_verbose_string(self)

Defines the pretty printing of all data in the circuit

plot(self, ax=None, f_data=None, Z_data=None, conf_bounds=None, scale=1, units='Ohms')

a convenience method for plotting Nyquist plots

Parameters:

f_data: np.array of type float

Frequencies of input data (for Bode plots)

Z_data: np.array of type complex

Impedance data to plot

conf_bounds: {‘error_bars’, ‘filled’, ‘filledx’, ‘filledy’}, optional

Include bootstrapped confidence bands (95%) on the predicted best fit model shown as either error bars or a filled confidence area. Confidence bands are estimated by simulating the spectra for 10000 randomly sampled parameter sets where each of the parameters is sampled from a normal distribution

Returns:

ax: matplotlib.axes

axes of the created nyquist plot

predict(self, frequencies, use_initial=False)

Predict impedance using a fit equivalent circuit model

Parameters:

frequencies: numpy array

Frequencies

use_initial: boolean

If true and a fit was already completed, use the initial parameters instead

Returns:

impedance: numpy array of dtype ‘complex128’

Predicted impedance

class impedance.circuits.CustomCircuit(circuit, **kwargs)

Methods

fit(self, frequencies, impedance[, method, …])	Fit the circuit model
get_param_names(self)	Converts circuit string to names
get_verbose_string(self)	Defines the pretty printing of all data in the circuit
plot(self[, ax, f_data, Z_data, …])	a convenience method for plotting Nyquist plots
predict(self, frequencies[, use_initial])	Predict impedance using a fit equivalent circuit model

class impedance.circuits.Randles(CPE=False, **kwargs)

A Randles circuit model class

Methods

fit(self, frequencies, impedance[, method, …])	Fit the circuit model
get_param_names(self)	Converts circuit string to names
get_verbose_string(self)	Defines the pretty printing of all data in the circuit
plot(self[, ax, f_data, Z_data, …])	a convenience method for plotting Nyquist plots
predict(self, frequencies[, use_initial])	Predict impedance using a fit equivalent circuit model