Functions to compare models and components. More...

#include "rwmodel.h"
#include "Matrix.h"

Functions
long	model_component_number_difference (Bmodel model1, Bmodel model2)
	Compares the numbers of components in two models. More...

long	model_maxnum_components (Bmodel *model)
	Calculates the largest number of components in a model. More...

double	model_compare (Bmodel model1, Bmodel model2)
	Compares two models. More...

Matrix	model_distance_matrix (Bmodel *model, int view_flag)
	Calculates the distance matrix for a model. More...

Matrix	model_distance_matrix (Bmodel m1, Bmodel m2)
	Calculates the distance matrix between two models. More...

Matrix	model_adjacency_matrix (Bmodel *model)
	Constructs the adjacency matrix for a model. More...

long	model_consolidate (Bmodel *model, double distance)
	Consolidates close components within a model. More...

Bmodel *	models_consensus (Bmodel *model, double distance)
	Determines a consensus between models in a list. More...

Detailed Description

Functions to compare models and components.

Author: Bernard Heymann

Date: Created: 20060908; Modified: 20161011

Function Documentation

◆ model_adjacency_matrix()

Matrix model_adjacency_matrix ( Bmodel * model )

Constructs the adjacency matrix for a model.

Parameters

*model model structure.

Returns

Matrix adjacency matrix.

The matrix contains ones for adjacent components and zero elsewhere. 
Only the first model in the linked list is used.
The component selections are reset.

◆ model_compare()

double model_compare	(	Bmodel *	model1,
		Bmodel *	model2
	)

Compares two models.

Parameters

*model1	first model structure.
*model2	second model structure.

Returns

double RMSD.

Only the first models in the linked lists are compared.

◆ model_component_number_difference()

long model_component_number_difference	(	Bmodel *	model1,
		Bmodel *	model2
	)

Compares the numbers of components in two models.

Parameters

*model1	first model.
*model2	second model.

Returns

long difference in the number of components.

Only the first models in the lists are compared.

◆ model_consolidate()

long model_consolidate	(	Bmodel *	model,
		double	distance
	)

Consolidates close components within a model.

Parameters

*model	model structure.
distance	cutoff distance to consider components to be the same.

Returns

long number of components retained.

A matrix is calculated from the pairwise distances between selected components.
Components closer to each other than the given distance are consolidated. 
Only the first model in the linked list is used.

◆ model_distance_matrix() [1/2]

Matrix model_distance_matrix	(	Bmodel *	m1,
		Bmodel *	m2
	)

Calculates the distance matrix between two models.

Parameters

*m1	first model structure.
*m2	second model structure.

Returns

Matrix distance matrix.

The matrix is calculated from the pairwise distances between selected 
components. 
Only the first model in each linked list is used.

◆ model_distance_matrix() [2/2]

Matrix model_distance_matrix	(	Bmodel *	model,
		int	view_flag
	)

Calculates the distance matrix for a model.

Parameters

*model	model structure.
view_flag	flag to include views.

Returns

Matrix distance matrix.

The matrix is calculated from the pairwise distances between selected 
components, with the option to include the views.
When the views are included, the euclidean distances are rescaled to
the maximum so that their ranges are similar to the view differences. 
Only the first model in the linked list is used.

◆ model_maxnum_components()

long model_maxnum_components ( Bmodel * model )

Calculates the largest number of components in a model.

Parameters

*model model.

Returns: long largest number of components in a model.

◆ models_consensus()

Bmodel * models_consensus	(	Bmodel *	model,
		double	distance
	)

Determines a consensus between models in a list.

Parameters

*model	model list.
distance	cutoff distance to consider components to be the same.

Returns

long number of components retained.

A matrix is calculated from the pairwise distances between selected components
from each apir of models.
Components closer to each other than the given distance in different
models are consolidated.
The component selection field contains the number of contributing components.
A new model containing the result is returned.