Module data

The N-state model or structural ensemble analysis base data handling.

Functions

list of str base_data_types()
Determine all the base data types.

float calc_ave_dist(atom1, atom2, exp=1)
Calculate the average distances.

int num_data_points()
Determine the number of data points used in the model.

(int, AlignTensorData instance) tensor_loop(red=False)
Generator method for looping over the full or reduced tensors.

Variables

__package__ = 'specific_analyses.n_state_model'

Imports: norm, is_float, RelaxError, interatomic_loop, return_spin, spin_loop

Function Details

base_data_types()

Determine all the base data types.

The base data types can include:

   - 'rdc', residual dipolar couplings.
   - 'pcs', pseudo-contact shifts.
   - 'noesy', NOE restraints.
   - 'tensor', alignment tensors.

Returns: list of str

A list of all the base data types.

calc_ave_dist(atom1, atom2, exp=1)

Calculate the average distances.

The formula used is:

             _N_
         / 1 \                  \ 1/exp
   <r> = | -  > |p1i - p2i|^exp |
         \ N /__                /
              i

where i are the members of the ensemble, N is the total number of structural models, and p1 and p2 at the two atom positions.

Parameters:

• atom1 (str) - The atom identification string of the first atom.
• atom2 (str) - The atom identification string of the second atom.
• exp (int) - The exponent used for the averaging, e.g. 1 for linear averaging and -6 for r^-6 NOE averaging.

Returns: float

The average distance between the two atoms.

num_data_points()

Determine the number of data points used in the model.

Returns: int

The number, n, of data points in the model.

tensor_loop(red=False)

Generator method for looping over the full or reduced tensors.

Parameters:

• red (bool) - A flag which if True causes the reduced tensors to be returned, and if False the full tensors are returned.

Returns: (int, AlignTensorData instance)

The tensor index and the tensor.