AnalysisBase#

class maicos.core.AnalysisBase(atomgroup: AtomGroup, unwrap: bool, refgroup: None | AtomGroup, jitter: float, concfreq: int, wrap_compound: str)[source]#

Bases: _Runner, 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.

During the analysis, the correlation time of an observable can be estimated to ensure that calculated errors are reasonable. For this, the _single_frame() method has to return a single float. For details on the computation of the correlation and its further analysis refer to maicos.lib.util.correlation_analysis().

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.

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

atomgroup#

A AtomGroup for which the calculations are performed.

Type:

MDAnalysis.core.groups.AtomGroup

_universe#

The Universe the AtomGroup belong to

Type:

MDAnalysis.core.universe.Universe

_trajectory#

The trajectory the AtomGroup 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

sums#

Sum of the observables across frames. Keys are the same as _obs.

Type:

MDAnalysis.analysis.base.Results

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

corrtime#

The correlation time of the analysed data. For details on how this is calculated see maicos.lib.util.correlation_analysis().

Type:

float

Raises:

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

Example

To write your own analysis module you can use the example given below. As with all MAICoS modules, this inherits from the maicos.core.base.AnalysisBase class.

The example will calculate the average box volume and stores the result within the result object of the class.

>>> import logging
>>> from typing import Optional

>>> import MDAnalysis as mda
>>> import numpy as np

>>> from maicos.core import AnalysisBase
>>> from maicos.lib.util import render_docs

Creating a logger makes debugging easier.

>>> logger = logging.getLogger(__name__)

In the following the analysis module itself. Due to the similar structure of all MAICoS modules you can render the parameters using the maicos.lib.util.render_docs() decorator. The decorator will replace special keywords with a leading $ with the actual docstring as defined in maicos.lib.util.DOC_DICT.

>>> @render_docs
... class NewAnalysis(AnalysisBase):
...     '''Analysis class calcuting the average box volume.'''
...
...     def __init__(
...         self,
...         atomgroup: mda.AtomGroup,
...         concfreq: int = 0,
...         temperature: float = 300,
...         output: str = "outfile.dat",
...     ):
...         super().__init__(
...             atomgroup=atomgroup,
...             refgroup=None,
...             unwrap=False,
...             jitter=0.0,
...             wrap_compound="atoms",
...             concfreq=concfreq,
...         )
...
...         self.temperature = temperature
...         self.output = output
...
...     def _prepare(self):
...         '''Set things up before the analysis loop begins.'''
...         # self.atomgroup refers to the provided `atomgroup`
...         # self._universe refers to full universe of given `atomgroup`
...         self.volume = 0
...
...     def _single_frame(self):
...         '''Calculate data from a single frame of trajectory.
...
...         Don't worry about normalising, just deal with a single frame.
...         '''
...         # Current frame index: self._frame_index
...         # Current timestep object: self._ts
...
...         volume = self._ts.volume
...         self.volume += volume
...
...         # Eeach module should return a characteristic scalar which is used
...         # by MAICoS to estimate correlations of an Analysis.
...         return volume
...
...     def _conclude(self):
...         '''Finalise the results you've gathered.
...
...         Called at the end of the run() method to finish everything up.
...         '''
...         self.results.volume = self.volume / self.n_frames
...         logger.info(
...             "Average volume of the simulation box "
...             f"{self.results.volume:.2f} ų"
...         )
...
...     def save(self) -> None:
...         '''Save results of analysis to file specified by ``output``.
...
...         Called at the end of the run() method after _conclude.
...         '''
...         self.savetxt(
...             self.output, np.array([self.results.volume]), columns="volume / ų"
...         )
...

Afterwards the new analysis can be run like this

>>> import MDAnalysis as mda
>>> from MDAnalysisTests.datafiles import TPR, XTC

>>> u = mda.Universe(TPR, XTC)

>>> na = NewAnalysis(u.atoms)
>>> _ = na.run(start=0, stop=10)
>>> round(na.results.volume, 2)
362631.65

Results can also be accessed by key

>>> round(na.results["volume"], 2)
362631.65
property box_center: ndarray#

Center of the simulation cell.

run(start: int | None = None, stop: int | None = None, step: int | None = None, frames: int | None = None, verbose: bool | None = None, progressbar_kwargs: dict | None = None) → Self[source]#

Iterate over the trajectory.

savetxt(fname: str, X: ndarray, columns: List[str] | None = None) → 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

  • atomgroup that was analyzed

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