gromacs.analysis.plugins.dist.Mindist

Class Mindist

object --+ | Mindist

The Mindist class allows analysis of the output from ``g_dist -dist CUTOFF``. Output is read from a file or stream. The raw data is transformed into a true 'mindist' time series (available in the :attr:`Mindist.distances` attribute): for each frame only the shortest distance is stored (whereas ``g_dist`` provides *all* distances below the cutoff). :TODO: * Save analysis to pickle or data files. * Export data as simple data files for plotting in other programs. .. Note:: :class:`gromacs.tools.G_mindist` is apparently providing exactly the service that is required: a timeseries of the minimum distance between two groups. Feel free to use that tool instead :-).

Instance Methods

[hide private]

__init__(self, datasource, cutoff=None)
Read mindist data from file or stream.

source code

histogram(self, nbins=None, lo=None, hi=None, midpoints=False, normed=True)
Returns a distribution or histogram of the minimum distances:

source code

plot(self, **kwargs)
Plot histograms with matplotlib's plot() function::

source code

Inherited from object: __delattr__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __str__

Class Variables

[hide private]

hist = property(** hist())

dist = property(** dist())

edges = property(** edges())

midpoints = property(** midpoints())

Properties

[hide private]

Inherited from object: __class__

init(self, datasource, cutoff=None)
(Constructor)

source code

Read mindist data from file or stream.

Overrides: object.__init__

Arguments:

datasource: a filename (plain, gzip, bzip2) or file object
cutoff: the -dist CUTOFF that was provided to g_dist; if supplied we work around a bug in g_dist (at least in Gromacs 4.0.2) in which sometimes numbers >> CUTOFF are printed.

histogram(self, nbins=None, lo=None, hi=None, midpoints=False, normed=True)

source code

Returns a distribution or histogram of the minimum distances:

If no values for the bin edges are given then they are set to 0.1 below and 0.1 above the minimum and maximum values seen in the data.

If the number of bins is not provided then it is set so that on average 100 counts come to a bin. Set nbins manually if the histogram only contains a single bin (and then get more data)!

Keywords:

nbins : int: number of bins
lo : float: lower edge of histogram
hi : float: upper edge of histogram
midpoints : boolean: False: return edges. True: return midpoints
normed : boolean: True: return probability distribution. False: histogram

plot(self, **kwargs)

source code

Plot histograms with matplotlib's plot() function::

   plot(**histogramargs, **plotargs)

Arguments for both :meth:`Mindist.histogram` and :func:`pylab.plot` can be provided (qv).

Class Mindist

__init__(self, datasource, cutoff=None) (Constructor)

histogram(self, nbins=None, lo=None, hi=None, midpoints=False, normed=True)

plot(self, **kwargs)

init(self, datasource, cutoff=None)
(Constructor)