Class N_state_model

Class for the N-state models.

Instance Methods

CoM(self, pivot_point=[0.0, 0.0, 0.0], centre=None)
Centre of mass (CoM) analysis.

cone_pdb(self, cone_type=None, scale=1.0, file='cone.pdb', dir=None, force=False)
Create a PDB file representing the cone models from the centre of mass (CoM) analysis.

elim_no_prob(self)
Eliminate the structures or states with no probability.

number_of_states(self, N=None)
Set the number of states in the N-state model.

ref_domain(self, ref=None)
Set the reference domain for the '2-domain' N-state model.

select_model(self, model=None)
Select the N-state model type and set up the model.

Inherited from base_class.User_fn_class: __init__

Method Details

CoM(self, pivot_point=[0.0, 0.0, 0.0], centre=None)

Centre of mass (CoM) analysis.

Keyword Arguments
~~~~~~~~~~~~~~~~~

pivot_point:  The pivot point of the motions between the two domains.

centre:  The optional argument for manually specifying the CoM of the initial position prior
         to the N rotations to the positions of the N states.


Description
~~~~~~~~~~~

This function is used for analysing the domain motion information content of the N states
from the N-state model.  The states do not correspond to physical states, hence nothing can
be extracted from the individual states.  This analysis involves the calculation of the
pivot to centre of mass (pivot-CoM) order parameter and subsequent cone of motions.

For the analysis, both the pivot point and centre of mass must be specified.  The supplied
pivot point must be a vector of floating point numbers of length 3.  If the centre keyword
argument is supplied, it must also be a vector of floating point numbers (of length 3).  If
the centre argument is not supplied, then the CoM will be calulcated from the selected parts
of a previously loaded structure.


Examples
~~~~~~~~

To perform an analysis where the pivot is at the origin and the CoM is set to the N-terminal
domain of a previously loaded PDB file (the C-terminal domain has been deselected), type:

relax> n_state_model.CoM()


To perform an analysis where the pivot is at the origin (because the real pivot has been
shifted to this position) and the CoM is at the position [0, 0, 1], type one of:

relax> n_state_model.CoM(centre=[0, 0, 1])
relax> n_state_model.CoM(centre=[0.0, 0.0, 1.0])
relax> n_state_model.CoM(pivot_point=[0.0, 0.0, 0.0], centre=[0.0, 0.0, 1.0])

cone_pdb(self, cone_type=None, scale=1.0, file='cone.pdb', dir=None, force=False)

Create a PDB file representing the cone models from the centre of mass (CoM) analysis.

Keyword Arguments
~~~~~~~~~~~~~~~~~

cone_type:  The type of cone model to represent.

scale:  Value for scaling the pivot-CoM distance which the size of the cone defaults to.

file:  The name of the PDB file.

dir:  The directory where the file is located.

force:  A flag which, if set to True, will overwrite the any pre-existing file.


Description
~~~~~~~~~~~

This function creates a PDB file containing an artificial geometric structure to represent
the various cone models.  These models include:

    'diff in cone'
    'diff on cone'

The model can be selected by setting the cone_type argument to one of these strings.  The
cone is represented as an isotropic cone with its axis parallel to the average pivot-CoM
vector, the vertex placed at the pivot point of the domain motions, and the length of the
edge of the cone equal to the pivot-CoM distance multipled by the scaling argument.  The
resultant PDB file can subsequently read into any molecular viewer.

There are four different types of residue within the PDB.  The pivot point is represented as
as a single carbon atom of the residue 'PIV'.  The cone consists of numerous H atoms of the
residue 'CON'.  The average pivot-CoM vector is presented as the residue 'AVE' with one
carbon atom positioned at the pivot and the other at the head of the vector (after scaling
by the scale argument).  Finally, if Monte Carlo have been performed, there will be multiple
'MCC' residues representing the cone for each simulation, and multiple 'MCA' residues
representing the varying average pivot-CoM vector for each simulation.

To create the diffusion in a cone PDB representation, a uniform distribution of vectors on a
sphere is generated using spherical coordinates with the polar angle defined from the
average pivot-CoM vector.  By incrementing the polar angle using an arccos distribution, a
radial array of vectors representing latitude are created while incrementing the azimuthal
angle evenly creates the longitudinal vectors.  These are all placed into the PDB file as H
atoms and are all connected using PDB CONECT records.  Each H atom is connected to its two
neighbours on the both the longitude and latitude.  This creates a geometric PDB object with
longitudinal and latitudinal lines representing the filled cone.

elim_no_prob(self)

Eliminate the structures or states with no probability.

Examples
~~~~~~~~

Simply type:

relax> n_state_model.elim_no_prob(N=8)

number_of_states(self, N=None)

Set the number of states in the N-state model.

Keyword Arguments
~~~~~~~~~~~~~~~~~

N:  The number of states.


Description
~~~~~~~~~~~

Prior to optimisation, the number of states in the N-state model can be specified.  If the
number of states is not set, then this parameter will be equal to the number of loaded
structures.


Examples
~~~~~~~~

To set up an 8-state model, type:

relax> n_state_model.number_of_states(N=8)

ref_domain(self, ref=None)

Set the reference domain for the '2-domain' N-state model.

Keyword Arguments
~~~~~~~~~~~~~~~~~

ref:  The domain which will act as the frame of reference.  This is only valid for the
'2-domain' N-state model.


Description
~~~~~~~~~~~

Prior to optimisation of the '2-domain' N-state model, which of the two domains will act as
the frame of reference must be specified.  The N-states will be rotations of the other
domain, so to switch the frame of reference to the other domain simply transpose the
rotation matrices.


Examples
~~~~~~~~

To set up a 5-state model with 'C' domain being the frame of reference, type:

relax> n_state_model.ref_domain(ref='C')

select_model(self, model=None)

Select the N-state model type and set up the model.

Keyword Arguments
~~~~~~~~~~~~~~~~~

model:  The name of the preset N-state model.


Description
~~~~~~~~~~~

Prior to optimisation, the N-state model type should be selected.  The preset models are:

'2-domain' - The N-state model for a system of two domains, where one domain experiences a
a reduced tensor.

'population' - The N-state model whereby only populations are optimised.  The structures
loaded into relax are assumed to be fixed.  I.e. if two domains are present, the Euler
angles for each state are fixed.  The parameters of the model include the weight or
probability for each state and the alignment tensor - {p0, p1, ..., pN, Axx, Ayy, Axy, Axz,
Ayz}.

'fixed' - The N-state model whereby all motions are fixed and all populations are fixed to
the set probabilities.  The parameters of the model are simply the alignment tensor, {Axx,
Ayy, Axy, Axz, Ayz}.


Examples
~~~~~~~~

To analyse populations of states, type:

relax> n_state_model.select_model(model='populations')