r2eff_ns_mmq_2site_sq_dq_zq(M0=None,
F_vector=array([ 1., 0.]),
R20A=None,
R20B=None,
pA=None,
dw=None,
dwH=None,
kex=None,
inv_tcpmg=None,
tcp=None,
back_calc=None,
num_points=None,
power=None)
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The 2-site numerical solution to the Bloch-McConnell equation for SQ,
ZQ, and DQ data.
The notation used here comes from:
-
Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav
Yu. Orekhov, and Lewis E. Kay (2005). Multiple-site exchange in
proteins studied with a suite of six NMR relaxation dispersion
experiments: An application to the folding of a Fyn SH3 domain
mutant. J. Am. Chem. Soc., 127, 15602-15611. (doi:
http://dx.doi.org/10.1021/ja054550e).
This function calculates and stores the R2eff values.
- Parameters:
M0 (numpy float64, rank-1, 7D array) - This is a vector that contains the initial magnetizations
corresponding to the A and B state transverse magnetizations.
F_vector (numpy rank-1, 2D float64 array) - The observable magnitisation vector. This defaults to [1, 0] for
X observable magnitisation.
R20A (numpy float array of rank [NS][NM][NO][ND]) - The transverse, spin-spin relaxation rate for state A.
R20B (numpy float array of rank [NS][NM][NO][ND]) - The transverse, spin-spin relaxation rate for state B.
pA (float) - The population of state A.
dw (numpy float array of rank [NS][NM][NO][ND]) - The combined chemical exchange difference between states A and B
in rad/s. It should be set to dwH for 1H SQ data, dw for
heteronuclear SQ data, dwH-dw for ZQ data, and dwH+dw for DQ
data.
dwH (numpy float array of rank [NS][NM][NO][ND]) - Unused - this is simply to match the r2eff_ns_mmq_2site_mq()
function arguments.
kex (float) - The kex parameter value (the exchange rate in rad/s).
inv_tcpmg (numpy float array of rank [NS][NM][NO][ND]) - The inverse of the total duration of the CPMG element (in inverse
seconds).
tcp (numpy float array of rank [NS][NM][NO][ND]) - The tau_CPMG times (1 / 4.nu1).
back_calc (numpy float array of rank [NS][NM][NO][ND]) - The array for holding the back calculated R2eff values. Each
element corresponds to one of the CPMG nu1 frequencies.
num_points (numpy int array of rank [NS][NM][NO]) - The number of points on the dispersion curve, equal to the length
of the tcp and back_calc arguments.
power (numpy int array of rank [NS][NM][NO][ND]) - The matrix exponential power array.
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