pyepr.relaxation_analysis

Attributes

cmap

Classes

CarrPurcellAnalysis	Analysis and calculation of Carr Purcell decay.
HahnEchoRelaxationAnalysis	Analysis, fitting and plotting for the HahnEchoRelaxation Sequence.
ReptimeAnalysis	Analysis and calculation of Reptime based saturation recovery.

Functions

detect_ESEEM(dataset[, type, threshold])	Detect if the dataset is an ESEEM experiment.
plot_1Drelax(*args[, fig, axs, cmap])	Create a superimposed plot of relaxation data and fits.

Module Contents

pyepr.relaxation_analysis.detect_ESEEM(dataset, type='deuteron', threshold=1.5)

Detect if the dataset is an ESEEM experiment.

Parameters:

datasetxr.DataArray

The dataset to be analyzed.

typestr, optional

The type of ESEEM experiment, either deuteron or proton, by default ‘deuteron’

thresholdfloat, optional

The SNR threshold for detection, by default 1.5

Returns:

bool

True if ESEEM is detected, False if not.

pyepr.relaxation_analysis.cmap = ['#D95B6F', '#42A399']

pyepr.relaxation_analysis.plot_1Drelax(*args, fig=None, axs=None, cmap=cmap)

Create a superimposed plot of relaxation data and fits.

Parameters:

argsad.Analysis

The 1D relaxation data to be plotted.

figFigure, optional

The figure to plot to, by default None

axsAxes, optional

The axes to plot to, by default None

cmaplist, optional

The color map to use, by default ad.cmap