Base class#

Base class for building Analysis classes.

class maicos.core.base.AnalysisBase(atomgroups, multi_group=False, refgroup=None, unwrap=False, jitter=None, concfreq=0)[source]#

Bases: AnalysisBase

Base class derived from MDAnalysis for defining multi-frame analysis.

The class is designed as a template for creating multi-frame analyses. This class will automatically take care of setting up the trajectory reader for iterating, and it offers to show a progress meter. Computed results are stored inside the results attribute. To define a new analysis, AnalysisBase needs to be subclassed and _single_frame() must be defined. It is also possible to define _prepare() and _conclude() for pre- and post-processing. All results should be stored as attributes of the MDAnalysis.analysis.base.Results container.

Parameters:

  • atomgroups (list[AtomGroup]) – a list of AtomGroup objects for which the calculations are performed.

  • refgroup (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 to the center of the (changing) box.

  • unwrap (bool) –

    When unwrap = 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.

  • 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

  • multi_group (bool) – Analysis is able to work with list of atomgroups

atomgroup#

Atomgroup taken for the Analysis (available if multi_group = False)

Type:

MDAnalysis.core.groups.AtomGroup

atomgroups#

Atomgroups taken for the Analysis (available if multi_group = True)

Type:

list[MDAnalysis.core.groups.AtomGroup]

n_atomgroups#

Number of atomngroups (available if multi_group = True)

Type:

int

_universe#

The Universe the atomgroups belong to

Type:

MDAnalysis.core.universe.Universe

_trajectory#

The trajectory the atomgroups belong to

Type:

MDAnalysis.coordinates.base.ReaderBase

times#

array of Timestep times. Only exists after calling AnalysisBase.run()

Type:

numpy.ndarray

frames#

array of Timestep frame indices. Only exists after calling AnalysisBase.run()

Type:

numpy.ndarray

_frame_index#

index of the frame currently analysed

Type:

int

_index#

Number of frames already analysed (same as _frame_index + 1)

Type:

int

results#

results of calculation are stored after call to AnalysisBase.run()

Type:

MDAnalysis.analysis.base.Results

_obs#

Observables of the current frame

Type:

MDAnalysis.analysis.base.Results

_obs.box_center#

Center of the simulation cell of the current frame

Type:

numpy.ndarray

means#

Means of the observables. Keys are the same as _obs.

Type:

MDAnalysis.analysis.base.Results

sems#

Standard errors of the mean of the observables. Keys are the same as _obs

Type:

MDAnalysis.analysis.base.Results

Raises:

ValueError – If any of the provided AtomGroups (atomgroups or refgroup) does not contain any atoms.

property box_center#

Center of the simulation cell.

run(start=None, stop=None, step=None, verbose=None)[source]#

Iterate over the trajectory.

Parameters:

  • start (int) – start frame of analysis

  • stop (int) – stop frame of analysis

  • step (int) – number of frames to skip between each analysed frame

  • verbose (bool) – Turn on verbosity

savetxt(fname, X, columns=None)[source]#

Save to text.

An extension of the numpy savetxt function. Adds the command line input to the header and checks for a doubled defined filesuffix.

Return a header for the text file to save the data to. This method builds a generic header that can be used by any MAICoS module. It is called by the save method of each module.

The information it collects is:

  • timestamp of the analysis

  • name of the module

  • version of MAICoS that was used

  • command line arguments that were used to run the module

  • module call including the default arguments

  • number of frames that were analyzed

  • atomgroups that were analyzed

  • output messages from modules and base classes (if they exist)

class maicos.core.base.ProfileBase(atomgroups, weighting_function, normalization, grouping, bin_method, output, f_kwargs=None)[source]#

Bases: object

Base class for computing profiles.

Parameters:

  • atomgroups (list[AtomGroup]) – a list of AtomGroup objects for which the calculations are performed.

  • grouping (str {'atoms', 'residues', 'segments', 'molecules', 'fragments'}) –

    Atom grouping for the calculations of profiles.

    The possible grouping options are the atom positions (in the case where grouping='atoms') or the center of mass of the specified grouping unit (in the case where grouping='residues', 'segments', 'molecules' or 'fragments').

  • bin_method (str {'cog', 'com', 'coc'}) –

    Method for the position binning.

    The possible options are center of geometry (cog), center of mass (com), and center of charge (coc).

  • output (str) – Output filename.

  • weighting_function (callable) – The function calculating the array weights for the histogram analysis. It must take an Atomgroup as first argument and a grouping (‘atoms’, ‘residues’, ‘segments’, ‘molecules’, ‘fragments’) as second. Additional parameters can be given as f_kwargs. The function must return a numpy.ndarray with the same length as the number of group members.

  • normalization (str {'None', 'number', 'volume'}) – The normalization of the profile performed in every frame. If None no normalization is performed. If number the histogram is divided by the number of occurences in each bin. If volume the profile is divided by the volume of each bin.

  • f_kwargs (dict) – Additional parameters for function

results.profile#

Calculated profile.

Type:

numpy.ndarray

results.dprofile#

Estimated profile’s uncertainity.

Type:

numpy.ndarray

save()[source]#

Save results of analysis to file.