reda.eis package

Submodules

reda.eis.convert module

reda.eis.convert.convert(input_format, output_format, data, one_spectrum=False)

Convert from the given format to the requested format

Parameters:

input_formatformat of input data (parameter ‘data’)

output_formatformat of output data

datanumpy array containing data in specified input format

one_spectrumTrue|False, the input data comprises one spectrum. This

allows for an additional format of the data array.

reda.eis.convert.from_ccomplex(data)

reda.eis.convert.from_cmag_cpha(data)

reda.eis.convert.from_cre_cim(data)

reda.eis.convert.from_cre_cmim(data)

reda.eis.convert.from_lnrmag_rpha(data)

reda.eis.convert.from_log10rmag_rpha(data)

reda.eis.convert.from_rcomplex(data)

reda.eis.convert.from_rmag_rpha(data)

reda.eis.convert.from_rre_rim(data)

reda.eis.convert.from_rre_rmim(data)

reda.eis.convert.generic_magpha_to_reim(mag, pha)

Generically convert magnitude and phase to real and imaginary part using the formula \(mag \cdot exp(1j / 1000 * pha)\)

Thus it is suitable for resistivities, multiply conductivity phases with -1

reda.eis.convert.split_data(data, squeeze=False)

Split 1D or 2D into two parts, using the last axis

Parameters:

data:

squeezesqueeze results to remove unnecessary dimensions

reda.eis.convert.to_ccomplex(cre, cim)

reda.eis.convert.to_cmag_cpha(cre, cim)

reda.eis.convert.to_complex(mag, pha)

reda.eis.convert.to_cre_cim(cre, cim)

reda.eis.convert.to_cre_cmim(cre, cim)

reda.eis.convert.to_lnrmag_rpha(cre, cim)

reda.eis.convert.to_log10rmag_rpha(cre, cim)

reda.eis.convert.to_rcomplex(cre, cim)

reda.eis.convert.to_rmag_rpha(cre, cim)

reda.eis.convert.to_rre_rim(cre, cim)

reda.eis.convert.to_rre_rmim(cre, cim)

reda.eis.plots module

class reda.eis.plots.multi_sip_response(objects=None, labels=None, obj_dict=None)

Bases: object

manage multiple sip_response objects and provide some nice overview plots

Methods

add(response[, label])	add one response object to the list
plot_rmag(filename[, pmin, pmax, title])	plot all resistance/resistivity magnitude spectra
plot_rpha(filename[, pmin, pmax, title])	plot all resistance/resistivity phase spectra

plot_cim
plot_cre
set_xlim

add(response, label=None)

add one response object to the list

plot_cim(filename, cmin=None, cmax=None, title=None)

plot_cre(filename, cmin=None, cmax=None, title=None)

plot_rmag(filename, pmin=None, pmax=None, title=None)

plot all resistance/resistivity magnitude spectra

plot_rpha(filename, pmin=None, pmax=None, title=None)

plot all resistance/resistivity phase spectra

set_xlim(xmin, xmax)

class reda.eis.plots.sip_response(frequencies, rcomplex=None, ccomplex=None, rmag=None, rpha=None, rmag_err=None, rpha_err=None)

Bases: object

Hold one EIS/SIP spectrum and return it in various formats

Methods

plot(filename[, title, reciprocal, limits, ...])	Standard plot of spectrum
to_one_line(array)	Flatten the array to one dimension using the 'F' (Fortran) style and return a 2D array

plot(filename, title=None, reciprocal=None, limits=None, dtype='rho', return_fig=False, **kwargs)

Standard plot of spectrum

Parameters:

filenamestr

Output filename. Include the ending to specify the filetype (usually .pdf or .png)

titlestring, optional

Title for the plot

reciprocalreda.eis.plots.sip_response, optional

If another reda.eis.plots.sip_response object is provided here, use this as the reciprocal spectrum.

limitsdict, optional

A dictionary which contains plot limits. See code example below.

dtypestring, optional

Determines if the data plotted included geometric factors (‘rho’) or not (‘r’). Default: ‘rho’

return_figbool, optional

If True, then do not delete the figure object after saving to file and return the figure object. Default: False

**kwargsdict

kwargs is piped through to the _plot function

Returns:

figmatplotlib.Figure

The figure object. Only returned if return_fig is set to True

Examples

>>> from reda.eis.plots import sip_response
>>> import numpy as np
>>> frequencies = np.array([
...     1.00000000e-03, 1.77827941e-03, 3.16227766e-03, 5.62341325e-03,
...     1.00000000e-02, 1.77827941e-02, 3.16227766e-02, 5.62341325e-02,
...     1.00000000e-01, 1.77827941e-01, 3.16227766e-01, 5.62341325e-01,
...     1.00000000e+00, 1.77827941e+00, 3.16227766e+00, 5.62341325e+00,
...     1.00000000e+01, 1.77827941e+01, 3.16227766e+01, 5.62341325e+01,
...     1.00000000e+02, 1.77827941e+02, 3.16227766e+02, 5.62341325e+02,
...     1.00000000e+03])
>>> rcomplex = np.array([
...     49.34369772-0.51828971j, 49.11781581-0.59248806j,
...     48.85819872-0.6331137j , 48.58762806-0.62835135j,
...     48.33331113-0.57965851j, 48.11599009-0.50083533j,
...     47.94405036-0.41005275j, 47.81528917-0.32210768j,
...     47.72215469-0.24543425j, 47.65607773-0.18297794j,
...     47.60962191-0.13433101j, 47.57706229-0.09755774j,
...     47.55424286-0.07031682j, 47.53822912-0.05041399j,
...     47.52697253-0.03601005j, 47.51904718-0.02565412j,
...     47.51345965-0.01824266j, 47.50951606-0.01295546j,
...     47.50673042-0.00919217j, 47.50476152-0.0065178j ,
...     47.50336925-0.00461938j, 47.50238442-0.00327285j,
...     47.50168762-0.00231829j, 47.50119454-0.00164187j,
...     47.50084556-0.00116268j])
>>> spectrum = sip_response(frequencies=frequencies, rcomplex=rcomplex)
>>> fig = spectrum.plot('spectrum.pdf', return_fig=True)

to_one_line(array)

Flatten the array to one dimension using the ‘F’ (Fortran) style and return a 2D array

reda.eis.test_convert module

Tests for converter functions

Run with

nosetests test_convert.py -s -v

class reda.eis.test_convert.TestClass_input_styles

Bases: object

Test the three input styles:

• 1D

• 2D - one spectrum

• 2D - multiple spectra

Methods

precompute_values
setup_method
test_input_styles

precompute_values()

setup_method()

test_input_styles()

class reda.eis.test_convert.TestClass_test_converters

Bases: object

Methods

test_convert()

We test by converting to all values, from all values.

check_from_function
check_to_function
precompute_values
setup_method
teardown
test_from_cmag_cpha
test_from_cre_cim
test_from_cre_cmim
test_from_rmag_rpha
test_from_rre_rim
test_from_rre_rmim
test_to_cmag_cpha
test_to_cre_cim
test_to_cre_mim
test_to_rre_rim

check_from_function(func, input1, input2)

check_to_function(func, output1, output2)

precompute_values()

setup_method()

classmethod teardown()

test_convert()

We test by converting to all values, from all values. This is a chain test, i.e. we only provide the first input data, and then we use the output of this conversion to feed the next conversion. The last conversion then converts back to the initial data format, and thus we can compare those outputs to the hardcoded values.

test_from_cmag_cpha()

test_from_cre_cim()

test_from_cre_cmim()

test_from_rmag_rpha()

test_from_rre_rim()

test_from_rre_rmim()

test_to_cmag_cpha()

test_to_cre_cim()

test_to_cre_mim()

test_to_rre_rim()

reda.eis.units module

reda.eis.units.get_label(parameter, ptype, flavor=None, mpl=None)

Return the label of a given SIP parameter

Parameters:

parameterstr

type of parameter, e.g. rmag|rpha|cre|cim

ptypestring

material|meas. Either return the material property (e.g. resistivity) or the measurement parameter (e.g., impedance)

flavorstring, optional

if set, must be one of latex|mathml. Return a label for latex processing, or for mathml processing

mplmatplotlib, optional

if set, infer flavor from mpl.rcParams. Will not be used if flavor is set

Returns:

labelstring

the requested label