4.11.1. Analysis data files

MDAnalysis.analysis.data contains data files that are used as part of analysis. These can be experimental or theoretical data. Files are stored inside the package and made accessible via variables in MDAnalysis.analysis.data.filenames. These variables are documented below, including references to the literature and where they are used inside MDAnalysis.analysis.

4.11.1.1. Data files

MDAnalysis.analysis.data.filenames.Rama_ref

Reference Ramachandran histogram for MDAnalysis.analysis.dihedrals.Ramachandran. The data were calculated on a data set of 500 PDB structures taken from [Lovell2003]. This is a numpy array in the \(\phi\) and \(\psi\) backbone dihedral angles.

Load and plot it with

import numpy as np
import matplotlib.pyplot as plt
from MDAnalysis.analysis.data.filenames import Rama_ref
X, Y = np.meshgrid(np.arange(-180, 180, 4), np.arange(-180, 180, 4))
Z = np.load(Rama_ref)
ax.contourf(X, Y, Z, levels=[1, 17, 15000])

The given levels will draw contours that contain 90% and 99% of the data points. See the Ramachandran plot figure as an example.

MDAnalysis.analysis.data.filenames.Janin_ref

Reference Janin histogram for MDAnalysis.analysis.dihedrals.Janin. The data were calculated on a data set of 500 PDB structures taken from [Lovell2003]. This is a numpy array in the \(\chi_1\) and \(\chi_2\) sidechain dihedral angles.

Load and plot it with

import numpy as np
import matplotlib.pyplot as plt
from MDAnalysis.analysis.data.filenames import Janin_ref
X, Y = np.meshgrid(np.arange(-180, 180, 4), np.arange(-180, 180, 4))
Z = np.load(Janin_ref)
ax.contourf(X, Y, Z, levels=[1, 6, 600])

The given levels will draw contours that contain 90% and 98% of the data. See the Janin plot figure as an example.