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Matplotlib DPL94 R1rho R2eff

871 bytes removed, 15:53, 6 November 2015
→‎References: Switched to a labelled section transclusion for the citations.
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== About ==
The production to these figures relates to the Suppport Request:<br>
[http://www.nmr-relax.com/manual/Dispersion_model_summary.html Refer to the manual for parameter explanation]
* {{# Evenäs, J., Malmendal, A. & Akke, M. (2001). Dynamics of the transition between open and closed conformations in a calmodulin C-terminal domain mutant. Structure 9, 185–195 [httplst://dx.doi.org/10.1016/S0969-2126(01)00575-5 DOI]Citations|Evenäs01}}* {{# Kempf, J.G. & Loria, J.P. (2004). Measurement of intermediate exchange phenomena. Methods Mol. Biol. 278, 185–231 [http://dx.doi.org/10.1385/1-59259-809-9lst:185 DOI]Citations|KempfLoria04}}* {{# Palmer, A.G. & Massi, F. (2006). Characterization of the dynamics of biomacromolecules using rotating-frame spin relaxation NMR spectroscopy. Chem. Rev. 106, 1700–1719 [httplst://dx.doi.org/10.1021/cr0404287 DOI]Citations|Massi05}}* {{# Palmer, A.G., Kroenke, C.D. & Loria, J.P. (2001). Nuclear magnetic resonance methods for quantifying microsecond-to-millisecond motions in biological macromolecules. Meth. Enzymol. 339 [httplst://dx.doi.org/10.1016/S0076-6879(01)39315-1 DOI]Citations|Palmer01}}* {{# Francesca Massi, Michael J. Grey, Arthur G. Palmer III* (2005) Microsecond timescale backbone conformational dynamics in ubiquitin studied with NMR R1ρ relaxation experiments, Protein science [httplst://dx.doi.org/10.1110/ps.041139505 DOI]Citations|PalmerMassi06}}
=== Figures ===
Ref [2], Equation 27.
Here the calculated value is noted as: $R_{eff{:Reff}$. : Equation 27: $ R_{eff} = R_{1\rho{:R1rho}} / sin^<sup>2</sup>(\thetaθ) - R_1 {{:R1}} / tan^<sup>2</sup>(\thetaθ) = R^{0{:R2zero}}_2 + R_{ex{:Rex}} $. <br>Where $R^, where {{0:R2zero}}_2$ refers to $R_{1\rho '{:R1rhoprime}}$ as seen at [[DPL94]]
Ref [3], Equation 20.
Here the calculated value is noted as: $R_2${{: $R_2 R2}} = R_{1\rho{:R1rho}} / sin^<sup>2</sup>(\thetaθ) - R_1 {{:R1}} / tan^<sup>2</sup>(\thetaθ)$ <br>. Figure 11+16, would be the reference.
Ref [4], Equation 43. $R_{eff{:Reff}} = R_{1\rho{:R1rho}} / sin^<sup>2</sup>(\thetaθ) - R_1 {{:R1}} / tan^<sup>2</sup>(\thetaθ)$.
Ref [5], Material and Methods, page 740. Here the calculated value is noted as: $R_2{{:R2}}: {{: R_2 R2}} = R^{0{:R2zero}}_2 + R_{ex{:Rex}}$. <br> Figure 4 would be the wished graphs.
=== The outcome ===
[[File:Matplotlib 52 N R1 rho theta sep.png|thumb|center|upright=2|Figure 1]][[File:Matplotlib 52 N R1 rho R2eff w eff.png|thumb|center|upright=2|Figure 2]][[File:Matplotlib 52 N R1 rho R2eff disp.png|thumb|center|upright=2|Figure 3]]
== To run ==
=== Code ===
File: '''{{Collapsible script| title = r1rhor2eff.py'''Python script<source | lang ="python">| script =
### python imports
import sys
ylabel_R1_rho = r'R$_{1\rho}$ [rad s$^{-1}$]'
ylabel_R1_rho_R2eff = r'R$_{1\rho}$, R_R$_{2,eff}}$ [rad s$^{-1}$]'
xlabel_theta = 'Rotating frame tilt angle [rad]'
plt.show()
</source>}}
== Bugs ? ==
== See also ==
[[Category:Matplotlib]]
[[Category:Relaxation_dispersionanalysis]]
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