Python based statistical learning of NMR tensor parameters distribution from 2D isotropic/anisotropic NMR correlation spectra.
Project description
Mrinversion
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The mrinversion
python package is based on the statistical learning technique for
determining the distribution of the magnetic resonance (NMR) tensor parameters
from the two-dimensional NMR spectra correlating the isotropic to anisotropic
resonances.
The library utilizes the mrsimulator
package for generating solid-state NMR lineshapes and
scikit-learn package for statistical learning.
Features
The mrinversion
package includes the inversion of a two-dimensional
solid-state NMR spectrum of dilute spin-systems to a three-dimensional distribution of
tensor parameters. At present, we support the inversion of
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Magic angle flipping (MAF) spectra correlating the isotropic chemical shift resonances to pure anisotropic resonances into a three-dimensional distribution of nuclear shielding tensor parameters---isotropic chemical shift, shielding anisotropy and asymmetry parameters---defined using the Haeberlen convention.
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Magic angle turning (MAT), Phase adjusted spinning sidebands (PASS), and similar spectra correlating the isotropic chemical shift resonances to pure anisotropic spinning sideband resonances into a three-dimensional distribution of nuclear shielding tensor parameters---isotropic chemical shift, shielding anisotropy and asymmetry parameters---defined using the Haeberlen convention.
For more information, refer to the documentation.
View our example gallery
Installation
$ pip install mrinversion
Please read our installation document for details.
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