aquaduct.traj.reader module

class Reader(topology, trajectory, window=None)

Bases: object

__init__(topology, trajectory, window=None)

open_trajectory()

real_number_of_frames

next_frame()

set_real_frame(frame)

get_start_frame()

get_step_frame()

get_stop_frame()

get_window_frame_range()

number_of_frames

iterate_over_frames()

cf2rf(cf)

set_current_frame(frame)

parse_selection(selection)

select_resnum(resnum)

select_multiple_resnum(resnum_list)

class ReadViaMDA(topology, trajectory, window=None)

Bases: aquaduct.traj.reader.Reader

set_real_frame(frame)

real_number_of_frames

next_frame()

parse_selection(selection)

select_resnum(resnum)

select_multiple_resnum(resnum_list)

__enter__()

__exit__(typ, value, traceback)

open_trajectory()

class ReadAmberNetCDFviaMDA(topology, trajectory, window=None)

Bases: aquaduct.traj.reader.ReadViaMDA

open_trajectory()

class ReadDCDviaMDA(topology, trajectory, window=None)

Bases: aquaduct.traj.reader.ReadViaMDA

open_trajectory()

VdW_radii = {‘ge’: 2.11, ‘gd’: 2.34, ‘ga’: 1.87, ‘la’: 2.43, ‘li’: 1.82, ‘tl’: 1.96, ‘lu’: 2.24, ‘lr’: 2.46, ‘th’: 2.45, ‘ti’: 2.11, ‘te’: 2.06, ‘tb’: 2.33, ‘tc’: 2.16, ‘ta’: 2.22, ‘yb’: 2.26, ‘dy’: 2.31, ‘xe’: 2.16, ‘h’: 1.1, ‘p’: 1.8, ‘tm’: 2.27, ‘zn’: 2.01, ‘eu’: 2.35, ‘es’: 2.45, ‘er’: 2.29, ‘ru’: 2.13, ‘re’: 2.16, ‘ra’: 2.83, ‘rb’: 3.03, ‘rn’: 2.2, ‘rh’: 2.1, ‘be’: 1.53, ‘ba’: 2.68, ‘bi’: 2.07, ‘bk’: 2.44, ‘br’: 1.85, ‘c’: 1.7, ‘k’: 2.75, ‘o’: 1.52, ‘s’: 1.8, ‘w’: 2.18, ‘os’: 2.16, ‘co’: 2.0, ‘cm’: 2.45, ‘cl’: 1.75, ‘ca’: 2.31, ‘cf’: 2.45, ‘ce’: 2.42, ‘cd’: 2.18, ‘cs’: 3.43, ‘cr’: 2.06, ‘cu’: 1.96, ‘pr’: 2.4, ‘pt’: 2.13, ‘pu’: 2.43, ‘pb’: 2.02, ‘pa’: 2.43, ‘pd’: 2.1, ‘po’: 1.97, ‘pm’: 2.38, ‘ho’: 2.3, ‘hf’: 2.23, ‘hg’: 2.23, ‘he’: 1.4, ‘md’: 2.46, ‘mg’: 1.73, ‘b’: 1.92, ‘f’: 1.47, ‘mo’: 2.17, ‘mn’: 2.05, ‘n’: 1.55, ‘v’: 2.07, ‘ac’: 2.47, ‘ag’: 2.11, ‘ir’: 2.13, ‘am’: 2.44, ‘al’: 1.84, ‘as’: 1.85, ‘ar’: 1.88, ‘au’: 2.14, ‘at’: 2.02, ‘in’: 1.93, ‘ni’: 1.97, ‘no’: 2.46, ‘na’: 2.27, ‘nb’: 2.18, ‘nd’: 2.39, ‘ne’: 1.54, ‘zr’: 2.23, ‘np’: 2.39, ‘fr’: 3.48, ‘y’: 2.32, ‘fe’: 2.04, ‘fm’: 2.45, ‘i’: 1.98, ‘sr’: 2.49, ‘kr’: 2.02, ‘si’: 2.1, ‘u’: 2.41, ‘sn’: 2.17, ‘sm’: 2.36, ‘sc’: 2.15, ‘sb’: 2.06, ‘se’: 1.9}

Dictionary of VdW radii.

Data taken from L. M. Mentel, mendeleev, 2014. Available at: https://bitbucket.org/lukaszmentel/mendeleev. Package mendeleev is not used because it depends on too many other libraries.

atom2vdw_radius(atom)

Function tries to guess atom element and checks if it is in VdW_radii dictionary. If it fails 1.4 is returned. Guessing is done twice:

1. Function MDAnalysis.topology.core.guess_atom_element() is used.
2. MDAnalysis.core.AtomGroup.Atom.element is used.

Parameters:atom (MDAnalysis.core.AtomGroup.Atom) – Atom of interest. Return type:float Returns:VdW radius.