Module parameters

The R1 and R2 exponential relaxation curve fitting parameter functions.

Functions

numpy array assemble_param_vector(spin=None, sim_index=None)
Assemble the exponential curve parameter vector (as a numpy array).

disassemble_param_vector(param_vector=None, spin=None, sim_index=None)
Disassemble the parameter vector.

linear_constraints(spin=None, scaling_matrix=None)
Set up the relaxation curve fitting linear constraint matrices A and b.

Variables

__package__ = 'specific_analyses.relax_fit'

Imports: array, float64, zeros, search

Function Details

assemble_param_vector(spin=None, sim_index=None)

Assemble the exponential curve parameter vector (as a numpy array).

Parameters:

• spin (SpinContainer instance) - The spin data container.
• sim_index (int) - The optional MC simulation index.

Returns: numpy array

An array of the parameter values of the exponential model.

disassemble_param_vector(param_vector=None, spin=None, sim_index=None)

Disassemble the parameter vector.

Parameters:

• param_vector (numpy array) - The parameter vector.
• spin (SpinContainer instance) - The spin data container.
• sim_index (int) - The optional MC simulation index.

linear_constraints(spin=None, scaling_matrix=None)

Set up the relaxation curve fitting linear constraint matrices A and b.

Standard notation

The relaxation rate constraints are:

   Rx >= 0

The intensity constraints are:

   I0 >= 0
   Iinf >= 0

Matrix notation

In the notation A.x >= b, where A is an matrix of coefficients, x is an array of parameter values, and b is a vector of scalars, these inequality constraints are:

   | 1  0  0 |     |  Rx  |      |    0    |
   |         |     |      |      |         |
   | 1  0  0 |  .  |  I0  |  >=  |    0    |
   |         |     |      |      |         |
   | 1  0  0 |     | Iinf |      |    0    |

Parameters:

• spin (SpinContainer instance) - The spin data container.
• scaling_matrix (numpy diagonal matrix) - The diagonal, square scaling matrix.