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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 two-dimensional NMR spectra correlating the isotropic to anisotropic frequencies. The library utilizes the mrsimulator package for generating solid-state NMR spectra 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

  • 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.

  • 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.

For more information, refer to the documentation.

View our example gallery

Installation

$ pip install mrinversion

Please read our installation document for details.

Project details


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