ADR suggestion Analysis

[henrikjacobsenfys]

General

The Analysis class is where fitting takes place. This ADR suggestions is a work in progress.

Current implementation

Only a skeleton has been implemented

Suggested implementation

The Analysis class will inherit from the EasyScience Analysis Class.

It will have at least the following methods:
set_sample_model Sets the model describing scattering from the sample, see #4
set_resolution_model Sets the model of the resolution, see #2
set_background_model Sets the model of the background. It will also be a SampleModel, but will not have detailed balancing, and will not be convolved with the resolution
set_data Sets the data. For now, only a single 1D dataset, later we will expand.
get_data returns the data (to be used for plotting)
plot_data
calculate_theory: Calculate the full model including background, resolution convolution. It will use the ResolutionHandler for this #2
calculate_theory_components: Calculate the individual components of SampleModel, as well as BackgroundModel for plotting
plot_full_model
plot_individual_components
fit Uses calculate_theory, EasyScience and get_fit_parameters
get_fit_parameters: Get all parameters for fitting, to be used by EasyScience

[damskii9992]

A few comments here. The set_resolution_model and set_background_model should probably just be a single set_instrument_model (see my comment on #2).
The set_data should be set_measurement or set_experiment which is where you attach the Measurement (or Experiment) class.
You can still have a get_data method, but it should then just be a shorthand for Analysis.Measurement.get_data()

[henrikjacobsenfys]

Good points! I'll make those changes when I make a proper Measurement class

[rozyczko]

Based on what was discussed in e.g. easyscience/EasyDiffractionLib#97
We shouldn't use set_ for properties.
Instead, set_sample_model should be sample_models.append() and sample_models.remove(), which also means that maybe your sample model should be actually a collection. Do you not envision having more than a single model?

Similar comment is to other setters, especially with data - set_data should probably be a bit more nuanced, as @damskii9992 mentioned.
Don't we want the Experiment (or Measurement) class to own the data, anyway?
I would suggest analysis.experiment.data.append() where data is also a collection (maybe a scipp data array?)