BGlib.gmode.analysis.GIVBayesian

class BGlib.gmode.analysis.GIVBayesian(h5_main, ex_freq, gain, num_x_steps=250, r_extra=110, **kwargs)[source]

A class that performs Bayesian inference to decouple spurious hysteresis signals from current-voltage spectroscopy signals in General mode I-V data

Applies Bayesian Inference to General Mode IV (G-IV) data to extract the true current

Parameters:

  • h5_main (h5py.Dataset object) – Dataset to process

  • ex_freq (float) – Frequency of the excitation waveform

  • gain (uint) – Gain setting on current amplifier (typically 7-9)

  • num_x_steps (uint (Optional, default = 250)) – Number of steps for the inferred results. Note: this may be end up being slightly different from specified.

  • r_extra (float (Optional, default = 110 [Ohms])) – Extra resistance in the RC circuit that will provide correct current and resistance values

  • h5_target_group (h5py.Group, optional. Default = None) – Location where to look for existing results and to place newly computed results. Use this kwarg if the results need to be written to a different HDF5 file. By default, this value is set to the parent group containing h5_main

  • kwargs (dict) – Other parameters specific to the Process class and nuanced bayesian_inference parameters

__init__(h5_main, ex_freq, gain, num_x_steps=250, r_extra=110, **kwargs)[source]

Applies Bayesian Inference to General Mode IV (G-IV) data to extract the true current

Parameters:

  • h5_main (h5py.Dataset object) – Dataset to process

  • ex_freq (float) – Frequency of the excitation waveform

  • gain (uint) – Gain setting on current amplifier (typically 7-9)

  • num_x_steps (uint (Optional, default = 250)) – Number of steps for the inferred results. Note: this may be end up being slightly different from specified.

  • r_extra (float (Optional, default = 110 [Ohms])) – Extra resistance in the RC circuit that will provide correct current and resistance values

  • h5_target_group (h5py.Group, optional. Default = None) – Location where to look for existing results and to place newly computed results. Use this kwarg if the results need to be written to a different HDF5 file. By default, this value is set to the parent group containing h5_main

  • kwargs (dict) – Other parameters specific to the Process class and nuanced bayesian_inference parameters

Methods

__init__(h5_main, ex_freq, gain[, ...])

Applies Bayesian Inference to General Mode IV (G-IV) data to extract the true current

compute([override])

Creates placeholders for the results, applies the inference to the data, and writes the output to the file.

test([pix_ind, show_plots])

Tests the inference on a single pixel (randomly chosen unless manually specified) worth of data.

use_partial_computation([h5_partial_group])

Extracts the necessary parameters from the provided h5 group to resume computation

Attributes

parms_dict

The name of the HDF5 dataset that should be present to signify which positions have already been computed This is NOT a fully private variable so that multiple processes can be run within a single group - Eg Fitter In the case of Fitter - this name can be changed from 'completed_guesses' to 'completed_fits' check_for_duplicates will be called by the Child class where they have the opportunity to change this variable before checking for duplicates