PlanarBase

class maicos.core.PlanarBase(atomgroup: AtomGroup, unwrap: bool, refgroup: AtomGroup | None, jitter: float, concfreq: int, dim: int, zmin: None | float, zmax: None | float, bin_width: float, wrap_compound: str)

Bases: AnalysisBase

Analysis class providing options and attributes for a planar system.

Parameters:

• atomgroup (MDAnalysis.core.groups.AtomGroup) – A AtomGroup for which the calculations are performed.

• unwrap (bool) –

  When True, molecules that are broken due to the periodic boundary conditions are made whole.

  If the input contains molecules that are already whole, speed up the calculation by disabling unwrap. To do so, use the flag -no-unwrap when using MAICoS from the command line, or use unwrap=False when using MAICoS from the Python interpreter.

  Note: Molecules containing virtual sites (e.g. TIP4P water models) are not currently supported in MDAnalysis. In this case, you need to provide unwrapped trajectory files directly, and disable unwrap. Trajectories can be unwrapped, for example, using the trjconv command of GROMACS.

• refgroup (MDAnalysis.core.groups.AtomGroup) – Reference AtomGroup used for the calculation. If refgroup is provided, the calculation is performed relative to the center of mass of the AtomGroup. If refgroup is None the calculations are performed with respect to the center of the (changing) box.

• jitter (float) –

  Magnitude of the random noise to add to the atomic positions.

  A jitter can be used to stabilize the aliasing effects sometimes appearing when histogramming data. The jitter value should be about the precision of the trajectory. In that case, using jitter will not alter the results of the histogram. If jitter = 0.0 (default), the original atomic positions are kept unchanged.

  You can estimate the precision of the positions in your trajectory with maicos.lib.util.trajectory_precision(). Note that if the precision is not the same for all frames, the smallest precision should be used.

• concfreq (int) – When concfreq (for conclude frequency) is larger than 0, the conclude function is called and the output files are written every concfreq frames.

• dim ({0, 1, 2}) – Dimension for binning (x=0, y=1, z=1).

• zmin (float) –

  Minimal coordinate for evaluation (in Å) with respect to the center of mass of the refgroup.

  If zmin=None, all coordinates down to the lower cell boundary are taken into account.

• zmax (float) –

  Maximal coordinate for evaluation (in Å) with respect to the center of mass of the refgroup.

  If zmax = None, all coordinates up to the upper cell boundary are taken into account.

• bin_width (float) – Width of the bins (in Å).

• wrap_compound (str) – The group which will be kept together through the wrap processes. Allowed values are: "atoms", "group", "residues", "segments", "molecules", or "fragments".

results.bin_pos

Bin positions (in Å) ranging from zmin to zmax.

Type:

numpy.ndarray

zmin

Minimal coordinate for evaluation (Å) with in the lab frame, where 0 corresponds to the origin of the cell.

Type:

float

zmax

Maximal coordinate for evaluation (Å) with in the lab frame, where 0 corresponds to the origin of the cell.

Type:

float

_obs.L

Average length (in Å) along the chosen dimension in the current frame.

Type:

float

_obs.bin_pos

Central bin positions (in Å) of each bin (in Å) in the current frame.

Type:

numpy.ndarray, (n_bins)

_obs.bin_width

Bin width (in Å) in the current frame

Type:

float

_obs.bin_edges

Edges of the bins (in Å) in the current frame.

Type:

numpy.ndarray, (n_bins + 1)

_obs.bin_area

Area of the rectangle of each bin in the current frame. Calculated via \(L_x \cdot L_y / N_\mathrm{bins}\) where \(L_x\) and \(L_y\) are the box lengths perpendicular to the dimension of evaluations given by dim. \(N_\mathrm{bins}\) is the number of bins.

Type:

numpy.ndarray, (n_bins)

results.bin_volume

Volume of an cuboid of each bin (in Å^3) in the current frame.

Type:

numpy.ndarray, (n_bins)

property odims: ndarray

Other dimensions perpendicular to dim i.e. (0,2) if dim = 1.