msmbuilder.metrics.Dihedral.__init__¶
- Dihedral.__init__(metric='euclidean', p=2, angles='phi/psi', userfilename='DihedralIndices.dat', V=None, VI=None, indices=None)¶
Create a distance metric to act on torison angles
Parameters: metric : {‘braycurtis’, ‘canberra’, ‘chebyshev’, ‘cityblock’,
‘correlation’, ‘cosine’, ‘euclidean’, ‘minkowski’, ‘sqeuclidean’, ‘seuclidean’, ‘mahalanobis’, ‘sqmahalanobis’}
Distance metric to equip the vector space with.
angles : {‘phi’, ‘psi’, ‘chi’, ‘omega’, ‘psi/psi’, etc... OR ‘user’ }
A slash separated list of strings specifying the types of angles to compute per residue. The choices are ‘phi’, ‘psi’, ‘chi’, and ‘omega’, or any combination thereof. If angles = ‘user’, indices are taken from the userfilename
userfilename: string, optional :
filename used for angles=user. Default is ‘DihderalIndices.dat’
p : int, optional
p-norm order, used for metric=’minkowski’
V : ndarray, optional
variances, used for metric=’seuclidean’
VI : ndarray, optional
inverse covariance matrix, used for metric=’mahalanobi’
indices : ndarray, optional
N x 4 numpy array of indices to be considered as dihedral angles. If provided, this overrrides the angles argument. The semantics of the array are that each row, indices[i], is an array of length 4 giving (in order) the indices of 4 atoms that together form a dihedral you want to monitor.
See also
fast_cdist, fast_pdist, scipy.spatial.distance