- class RefocusedEcho2DAnalysis(dataset, sequence=None)¶
Analysis and calculation of Refocused Echo 2D data.
- Parameters:
- dataset
The dataset to be analyzed.
- sequenceSequence, optional
The sequence object describing the experiment. (not currently used)
- axis = '[]'¶
- data¶
- dataset¶
- _smooth(elements=3)¶
Used SVD to smooth the 2D data.
- Parameters:
- elementsint, optional
The number of elements to use in the smoothing, by default 3
- Returns:
- np.ndarray
The smoothed data.
- plot2D(contour=True, smooth=False, norm='Normal', axs=None, fig=None)¶
Create a 2D plot of the 2D relaxation data.
- Parameters:
- contourbool, optional
Plot the contour of the data, by default True
- normstr, optional
Normalise the data, by default ‘Normal’. Options are ‘Normal’ and ‘tau2’. With ‘tau2’ normalisation, the data is normalised to the maximum of each row.
- axsAxes, optional
The axes to plot to, by default None
- figFigure, optional
The figure to plot to, by default None
- plot1D(axs=None, fig=None)¶
Create a 1D plot of the 2D relaxation data.
- Parameters:
- axsAxes, optional
The axes to plot to, by default None
- figFigure, optional
The figure to plot to, by default None
- find_optimal(type, SNR_target, target_time, target_step, averages=None)¶
Calculate the optimal inter pulse delay for a given total measurment time, using either 4pulse or 5pulse data.
- Parameters:
- typestr
The type of data to use, either ‘4pDEER’ or ‘5pDEER’
- SNR_targetfloat
The Signal to Noise ratio target.
- target_timefloat
The target time in hours
- target_step: float
The target step size in ns.
- averagesint, optional
The total number of shots taken, by default None. If None, the number of shots will be calculated from the dataset.
- Returns:
- tau1: float
The calculated optimal tau1 in us
- tau2: float
The calculated optimal tau2 in us
- optimal_tau1(tau2=None)¶
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