BGlib.be.analysis.fitter.Fitter

class BGlib.be.analysis.fitter.Fitter(h5_main, proc_name, variables=None, **kwargs)[source]

Bases: Process

Creates a new instance of the abstract Fitter class

Parameters:

  • h5_main (h5py.Dataset or pyUSID.io.USIDataset object) – Main datasets whose one or dimensions will be reduced

  • proc_name (str or unicode) – Name of the child process

  • variables (str or list, optional) – List of spectroscopic dimension names that will be reduced

  • 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) – Keyword arguments that will be passed on to pyUSID.processing.process.Process

Methods

compute

Creates placeholders for the results, applies the _unit_computation() to chunks of the dataset

do_fit

Computes the Fit

do_guess

Computes the Guess

set_up_fit

Performs necessary book-keeping before do_fit can be called

set_up_guess

Performs necessary book-keeping before do_guess can be called

test

Tests the process on a subset (for example a pixel) of the whole data.

use_partial_computation

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
compute(override=False, *args, **kwargs)

Creates placeholders for the results, applies the _unit_computation() to chunks of the dataset

Parameters:

  • override (bool, optional. default = False) – By default, compute will simply return duplicate results to avoid recomputing or resume computation on a group with partial results. Set to True to force fresh computation.

  • args (list) – arguments to the mapped function in the correct order

  • kwargs (dict) – keyword arguments to the mapped function

Returns:

h5_results_grp – Group containing all the results

Return type:

h5py.Group

do_fit(*args, override=False, **kwargs)[source]

Computes the Fit

Parameters:

  • args (list, optional) – List of arguments

  • override (bool, optional) – If True, computes a fresh guess even if existing Fit was found Else, returns existing Fit dataset. Default = False

  • kwargs (dict, optional) – Keyword arguments

Returns:

HDF5 dataset with the Fit computed

Return type:

USIDataset

do_guess(*args, override=False, **kwargs)[source]

Computes the Guess

Parameters:

  • args (list, optional) – List of arguments

  • override (bool, optional) – If True, computes a fresh guess even if existing Guess was found Else, returns existing Guess dataset. Default = False

  • kwargs (dict, optional) – Keyword arguments

Returns:

HDF5 dataset with the Guesses computed

Return type:

USIDataset

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

set_up_fit(h5_partial_fit=None, h5_guess=None)[source]

Performs necessary book-keeping before do_fit can be called

Parameters:

  • h5_partial_fit (h5py.Dataset or pyUSID.io.USIDataset, optional) – HDF5 dataset containing partial Fit. Not implemented

  • h5_guess (h5py.Dataset or pyUSID.io.USIDataset, optional) – HDF5 dataset containing completed Guess. Not implemented

set_up_guess(h5_partial_guess=None)[source]

Performs necessary book-keeping before do_guess can be called

Parameters:

h5_partial_guess (h5py.Dataset or pyUSID.io.USIDataset, optional) – HDF5 dataset containing partial Guess. Not implemented

test(**kwargs)

Tests the process on a subset (for example a pixel) of the whole data. The class can be re-instantiated with improved parameters and tested repeatedly until the user is content, at which point the user can call compute() on the whole dataset.

Notes

This is not a function that is expected to be called in MPI

Parameters:

  • dict (kwargs -) – keyword arguments to test the process

  • optional – keyword arguments to test the process

use_partial_computation(h5_partial_group=None)

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

Parameters:

h5_partial_group (h5py.Group) – Group containing partially computed results