LowRank.Decomposition

LowRank.LowRankInfo.py

This module contains the class LowRankInfo, which is used to store information about the components of a SecSaxsData, which is mathematically interpreted as a low rank approximation of a matrix.

class Decomposition(ssd, xr_icurve, xr_ccurves, uv_icurve, uv_ccurves, mapped_curve=None, paired_ranges=None, **kwargs)

Bases: object

A class to store the result of decomposition which is a low rank approximation.

The result includes both components of X-ray and UV data and their associated information.

ssd

The SecSaxsData object from which the decomposition was performed.

Type:

SecSaxsData

xr

The XrData object from the SecSaxsData.

Type:

XrData

xr_icurve

The i-curve used for the decomposition of the X-ray data.

Type:

Curve

xr_ccurves

The component curves for the X-ray data.

Type:

list of Curve

xr_ranks

The ranks for each component of the X-ray data. If None, default ranks are used.

Type:

list of int or None

uv

The UvData object from the SecSaxsData.

Type:

UvData

uv_icurve

The i-curve used for the decomposition of the UV data.

Type:

Curve

uv_ccurves

The component curves for the UV data.

Type:

list of Curve

uv_ranks

The ranks for each component of the UV data. If None, default ranks are used.

Type:

list of int or None

mapping

The mapping information between the X-ray and UV data.

Type:

MappingInfo

mapped_curve

The mapped curve from the X-ray to UV domain. If None, it can be computed when needed.

Type:

MappedCurve or None

paired_ranges

The paired ranges for the X-ray and UV data. If None, it can be computed when needed.

Type:

list of PairedRange or None

num_components

The number of components in the decomposition.

Type:

int

Initialize the Decomposition object.

Parameters:

• ssd (SecSaxsData) – The SecSaxsData object from which the decomposition was performed.

• xr_icurve (Curve) – The i-curve used for the decomposition of the X-ray data.

• xr_ccurves (list of Curve) – The component curves for the X-ray data.

• uv_icurve (Curve) – The i-curve used for the decomposition of the UV data.

• uv_ccurves (list of Curve) – The component curves for the UV data.

• mapped_curve (MappedCurve, optional) – The mapped curve from the X-ray to UV domain. If None, it can be computed when needed.

• paired_ranges (list of PairedRange, optional) – The paired ranges for the X-ray and UV data. If None, it can be computed when needed.

• kwargs (dict, optional) – Additional keyword arguments (not used).

copy_with_new_components(xr_ccurves, uv_ccurves)

Create a new Decomposition with new component curves.

Parameters:

• xr_ccurves (list of Curve) – The new component curves for the X-ray data.

• uv_ccurves (list of Curve) – The new component curves for the UV data.

Returns:

A new Decomposition object with the specified component curves.

Return type:

Decomposition

get_num_components()

Get the number of components.

Returns:

The number of components in the decomposition.

Return type:

int

plot_components(title=None, **kwargs)

Plot the components.

Parameters:

title (str, optional) – If specified, add a super title to the plot.

Returns:

result – A PlotResult object which contains the following attributes.

• fig: The matplotlib Figure object.

• axes: A list of Axes objects.

Return type:

PlotResult

update_xr_ranks(ranks, debug=False)

Update the ranks for the X-ray data.

Default ranks are one for each component which means that interparticle interactions are not considered. This method allows the user to set different ranks for each component.

Parameters:

ranks (list of int) – The ranks for each component.

Return type:

None

get_xr_matrices(debug=False)

Get the matrices for the X-ray data.

Parameters:

debug (bool, optional) – If True, enable debug mode.

Return type:

tuple of (np.ndarray, np.ndarray, np.ndarray, np.ndarray)

get_xr_components(debug=False)

Get the components for the X-ray data.

Parameters:

debug (bool, optional) – If True, enable debug mode.

Returns:

The list of XrComponent objects.

Return type:

list of XrComponent

get_guinier_objects()

Get the list of Guinier objects for the XR components.

Returns:

The list of Guinier objects for each XR component.

Return type:

list of Guinier

get_rgs()

Get the list of Rg values for the XR components.

Returns:

The list of Rg values for each XR component.

Return type:

list of float

get_uv_matrices(debug=False)

Get the matrices for the UV data.

Parameters:

debug (bool, optional) – If True, enable debug mode.

Returns:

The matrices for the UV data.

Return type:

tuple of (np.ndarray, np.ndarray, np.ndarray, np.ndarray)

get_uv_components(debug=False)

Get the components for the UV data.

Return type:

List of UvComponent objects.

get_pairedranges(mapped_curve=None, area_ratio=0.7, concentration_datatype=2, debug=False)

Get the paired ranges.

Parameters:

• mapped_curve (MappedCurve, optional) – If specified, use this mapped curve instead of computing a new one.

• area_ratio (float, optional) – The area ratio for the range computation.

• concentration_datatype (int, optional) – The concentration datatype for the range computation.

• debug (bool, optional) – If True, enable debug mode.

Returns:

The list of PairedRange objects.

Return type:

list of PairedRange

get_proportions()

Get the proportions of the components.

Returns:

The proportions of the components as a numpy array.

Return type:

np.ndarray

compute_scds(debug=False)

Get the list of SCDs (Score of Concentration Dependence) for the decomposition.

Returns:

The list of SCD values for each component.

Return type:

list of float

get_cd_color_info()

Get the color information for the concentration dependence.

Returns:

• peak_top_xes (list of float) – The list of peak top x values for each component.

• scd_colors (list of str) – The list of colors for each component based on their ranks.

optimize_with_model(model_name, debug=False)

Optimize the decomposition with a model.

Parameters:

• model_name (str) –

  The name of the model to use for optimization.

  Supported models:

  • SDM: Stochastic Dispersive Model

  • EDM: Equilibrium Dispersive Model

• debug (bool, optional) – If True, enable debug mode.

Returns:

result – A new Decomposition object with optimized components.

Return type:

Decomposition