rmsFit

superimpose 2 structures iteratively

Functions Overview

findTransformation Match two arrays by rotation and translation.
match Matches two arrays onto each other, while iteratively removing outliers.
rowDistances Calculate the distances between the items of two arrays (of same shape) after least-squares superpositioning.
svd Singular Value Decomposition.

Classes Overview


rmsFit Module Details

biskit.rmsFit.findTransformation(x, y)[source]

Match two arrays by rotation and translation. Returns the rotation matrix and the translation vector.

Parameters:
  • x (array('f')) – first set of coordinates
  • y (array('f')) – second set of coordinates
Returns:

rotation matrix (3x3) and translation vector (1x3)

Return type:

array, array

biskit.rmsFit.match(x, y, n_iterations=1, z=2, eps_rmsd=0.5, eps_stdv=0.05)[source]

Matches two arrays onto each other, while iteratively removing outliers. Superimposed array y would be C{ N0.dot(y, N0.transpose(r)) + t }.

Parameters:
  • n_iterations (1|0) – number of calculations:: 1 .. no iteration 0 .. until convergence
  • z (float) – number of standard deviations for outlier definition (default: 2)
  • eps_rmsd (float) – tolerance in rmsd (default: 0.5)
  • eps_stdv (float) – tolerance in standard deviations (default: 0.05)
Returns:

(r,t), [ [percent_considered, rmsd_for_it, outliers] ]

Return type:

(array, array), [float, float, int]

biskit.rmsFit.rowDistances(x, y)[source]

Calculate the distances between the items of two arrays (of same shape) after least-squares superpositioning.

Parameters:
  • x (array('f')) – first set of coordinates
  • y (array('f')) – second set of coordinates
Returns:

array( len(x), ‘f’ ), distance between x[i] and y[i] for all i

Return type:

array