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"""A module to produce a domain boundary plot"""
from __future__ import division
from __future__ import print_function
__author__ = "Felix Simkovic"
__date__ = "23 Feb 2017"
__version__ = "0.1"
import matplotlib.pyplot as plt
import numpy as np
import warnings
from conkit.plot._figure import Figure
from conkit.plot._plottools import ColorDefinitions
[docs]class ContactDensityFigure(Figure):
"""A Figure object specifically for a contact density illustration.
This figure is an adaptation of the algorithm published by Sadowski
(2013) [#]_.
.. [#] Sadowski M. (2013). Prediction of protein domain boundaries
from inverse covariances. Proteins 81(2), 253-260.
Attributes
----------
hierarchy : :obj:`ContactMap <conkit.core.ContactMap>`
The default contact map hierarchy
bw_method : str
The method to estimate the bandwidth
Examples
--------
>>> import conkit
>>> cmap = conkit.io.read('toxd/toxd.mat', 'ccmpred').top_map
>>> conkit.plot.ContactDensityFigure(cmap)
"""
def __init__(self, hierarchy, bw_method='bowman', **kwargs):
"""A new contact density plot
Parameters
----------
hierarchy : :obj:`ContactMap <conkit.core.ContactMap>`
The default contact map hierarchy
bw_method : str, optional
The method to estimate the bandwidth [default: bowman]
**kwargs
General :obj:`Figure <conkit.plot._Figure.Figure>` keyword arguments
"""
super(ContactDensityFigure, self).__init__(**kwargs)
self._bw_method = None
self._hierarchy = None
self.bw_method = bw_method
self.hierarchy = hierarchy
self._draw()
def __repr__(self):
return "{0}(file_name=\"{1}\" bw_method=\"{2}\")".format(self.__class__.__name__, self.file_name,
self.bw_method)
@property
def bw_method(self):
"""The method to estimate the bandwidth
For a full list of options, please refer to
:func:`calculate_contact_density() <conkit.core.ContactMap.calculate_contact_density>`
"""
return self._bw_method
@bw_method.setter
def bw_method(self, bw_method):
"""Define the method to estimate the bandwidth"""
self._bw_method = bw_method
@property
def hierarchy(self):
"""A ConKit :obj:`ContactMap <conkit.core.ContactMap>`"""
return self._hierarchy
@hierarchy.setter
def hierarchy(self, hierarchy):
"""Define the ConKit :obj:`ContactMap <conkit.core.ContactMap>`
Raises
------
RuntimeError
The hierarchy is not an contact map
"""
if hierarchy:
Figure._check_hierarchy(hierarchy, "ContactMap")
self._hierarchy = hierarchy
def _draw(self):
"""Draw the actual plot"""
fig, ax = plt.subplots()
dens = np.asarray(self.hierarchy.calculate_contact_density(self.bw_method))
residues = np.asarray(
list(set(sorted([c.res1_seq for c in self.hierarchy] + [c.res2_seq for c in self.hierarchy]))))
x = np.arange(residues.min(), residues.max())
ax.plot(x, dens, linestyle="solid", color=ColorDefinitions.GENERAL, label="Kernel Density Estimate", zorder=2)
try:
import scipy.signal
line_kwargs = dict(linestyle="--", linewidth=1.0, alpha=0.5, color=ColorDefinitions.MISMATCH, zorder=1)
for minimum in scipy.signal.argrelmin(dens, order=1)[0]:
ax.axvline(x[minimum], **line_kwargs)
ax.axvline(0, ymin=0, ymax=0, label="Domain Boundary", **line_kwargs)
except ImportError:
warnings.warn("SciPy not installed - cannot determine local minima")
ax.set_xlim(x.min(), x.max())
ax.set_ylim(0., dens.max())
ax.set_xlabel('Residue number')
ax.set_ylabel('Kernel Density Estimate')
ax.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3, ncol=3, mode="expand", borderaxespad=0., scatterpoints=1)
aspectratio = Figure._correct_aspect(ax, 0.3)
ax.set(aspect=aspectratio)
fig.tight_layout()
fig.savefig(self.file_name, bbox_inches='tight', dpi=self.dpi)