relax_disp.select_model

Synopsis

Select the relaxation dispersion model.

Defaults

relax_disp.select_model(model=`R2eff')

Keyword arguments

model: The type of relaxation dispersion model to fit.

Description

A number of different dispersion models are supported. This includes both analytic models and numerical models. Models which are independent of the experimental data type are:

`R2eff' -

This is the model used to determine the R2eff/R1rho values and errors required as the base data for all other models,

The no chemical exchange models

`No R_ex' -

This is the model for no chemical exchange being present.

The SQ CPMG-type experiments

The currently supported analytic models are:

`LM63' -

The original Luz and Meiboom (1963) 2-site fast exchange equation with parameters {R20, ..., φ_ex, kex},

`LM63 3-site' -

The original Luz and Meiboom (1963) 3-site fast exchange equation with parameters {R20, ..., φ_ex, kex, φ_ex2, kex2},

`CR72' -

The reduced Carver and Richards (1972) 2-site equation for most time scales whereby the simplification R20A = R20B is assumed. The parameters are {R20, ..., pA, dw, kex},

`CR72 full' -

The full Carver and Richards (1972) 2-site equation for most time scales with parameters {R20A, R20B, ..., pA, dw, kex},

`IT99' -

The Ishima and Torchia (1999) 2-site model for all time scales with pA > > pB and with parameters {R20, ..., pA, dw, kex},

`TSMFK01' -

The Tollinger, Kay et al. (2001) 2-site very-slow exchange model, range of microsecond to second time scale. Applicable in the limit of slow exchange, when |R20A-R20B| < < k_AB,kB < < 1/tau_CP. R20A is the transverse relaxation rate of site A in the absence of exchange. 2*tau_CP is is the time between successive 180 deg. pulses. The parameters are {R20A, ..., dw, k_AB}.

`B14' -

The Baldwin (2014) 2-site exact solution model for all time scales, whereby the simplification R20A = R20B is assumed. The parameters are {R20, ..., pA, dw, kex},

`B14 full' -

The Baldwin (2014) 2-site exact solution model for all time scales with parameters {R20A, R20B, ..., pA, dw, kex},

The currently supported numeric models are:

`NS CPMG 2-site 3D' -

The reduced numerical solution for the 2-site Bloch-McConnell equations using 3D magnetisation vectors whereby the simplification R20A = R20B is assumed. Its parameters are {R20, ..., pA, dw, kex},

`NS CPMG 2-site 3D full' -

The full numerical solution for the 2-site Bloch-McConnell equations using 3D magnetisation vectors. Its parameters are {R20A, R20B, ..., pA, dw, kex},

`NS CPMG 2-site star' -

The reduced numerical solution for the 2-site Bloch-McConnell equations using complex conjugate matrices whereby the simplification R20A = R20B is assumed. It has the parameters {R20, ..., pA, dw, kex},

`NS CPMG 2-site star full' -

The full numerical solution for the 2-site Bloch-McConnell equations using complex conjugate matrices with parameters {R20A, R20B, ..., pA, dw, kex},

`NS CPMG 2-site expanded' -

The numerical solution for the 2-site Bloch-McConnell equations expanded using Maple by Nikolai Skrynnikov. It has the parameters {R20, ..., pA, dw, kex}.

The MMQ CPMG-type experiments

The currently supported models are:

`MMQ CR72' -

The the Carver and Richards (1972) 2-site model for most time scales expanded for MMQ CPMG data by Korzhnev et al., 2004, whereby the simplification R20A = R20B is assumed. Its parameters are {R20, ..., pA, dw, dwH, kex}.

`NS MMQ 2-site' -

The numerical solution for the 2-site Bloch-McConnell equations for combined proton-heteronuclear SQ, ZQ, DQ, and MQ CPMG data whereby the simplification R20A = R20B is assumed. Its parameters are {R20, ..., pA, dw, dwH, kex}.

`NS MMQ 3-site linear' -

The numerical solution for the 3-site Bloch-McConnell equations linearised with kAC = kCA = 0 for combined proton-heteronuclear SQ, ZQ, DQ, and MQ CPMG data whereby the simplification R20A = R20B = R20C is assumed. Its parameters are {R20, ..., pA, dw(AB), dwH(AB), kex(AB), pB, dw(BC), dwH(BC), kex(BC)}.

`NS MMQ 3-site' -

The numerical solution for the 3-site Bloch-McConnell equations for combined proton-heteronuclear SQ, ZQ, DQ, and MQ CPMG data whereby the simplification R20A = R20B = R20C is assumed. Its parameters are {R20, ..., pA, dw(AB), dwH(AB), kex(AB), pB, dw(BC), dwH(BC), kex(BC), kex(AC)}.

The R1rho-type experiments

The currently supported analytic models are:

On-resonance models are:

`M61' -

The Meiboom (1961) 2-site fast exchange equation with parameters {R1rho', ..., φ_ex, kex},

`M61 skew' -

The Meiboom (1961) 2-site equation for all time scales with pA > > pB and with parameters {R1rho', ..., pA, dw, kex},

Off-resonance models are:

`DPL94' -

The Davis, Perlman and London (1994) 2-site fast exchange equation with parameters {R1rho', ..., φ_ex, kex},

`TP02' -

The Trott and Palmer (2002) 2-site equation for all time scales with parameters {R1rho', ..., pA, dw, kex}.

`TAP03' -

The Trott, Abergel and Palmer (2003) off-resonance 2-site equation for all time scales with parameters {R1rho', ..., pA, dw, kex}.

`MP05' -

The Miloushev and Palmer (2005) 2-site off-resonance equation for all time scales with parameters {R1rho', ..., pA, dw, kex}.

The currently supported numeric models are:

`NS R1rho 2-site' -

The numerical solution for the 2-site Bloch-McConnell equations using 3D magnetisation vectors whereby the simplification R20A = R20B. Its parameters are {R1rho', ..., pA, dw, kex}.

`NS R1rho 3-site linear' -

The numerical solution for the 3-site Bloch-McConnell equations using 3D magnetisation vectors whereby the simplification R20A = R20B = R20C is assumed and linearised with kAC = kCA = 0. Its parameters are {R1rho', ..., pA, dw(AB), kex(AB), pB, dw(BC), kex(BC)}.

`NS R1rho 3-site' -

The numerical solution for the 3-site Bloch-McConnell equations using 3D magnetisation vectors. Its parameters are {R1rho', ..., pA, dw(AB), kex(AB), pB, dw(BC), kex(BC), kex(AC)}.

Prompt examples

To pick the 2-site fast exchange model for all selected spins, type one of:

[numbers=none]
relax> relax_disp.select_model('LM63')

[numbers=none]
relax> relax_disp.select_model(model='LM63')