Source code for conkit.plot.contactmap
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"""A module to produce a contact map plot"""
from __future__ import division
from __future__ import print_function
__author__ = "Felix Simkovic"
__date__ = "10 Jan 2018"
__version__ = "0.13.3"
import matplotlib.collections as mcoll
import matplotlib.pyplot as plt
import numpy as np
from conkit.core.struct import Gap
from conkit.misc import normalize
from conkit.plot.figure import Figure
from conkit.plot.tools import ColorDefinitions, _isinstance
[docs]class ContactMapFigure(Figure):
"""A Figure object specifically for a :obj:`~conkit.core.contactmap.ContactMap`
This figure will illustrate the contacts in a contact
map. This plot is a very common representation of contacts.
With this figure, you can illustrate either your contact
map by itself, compared against a second contact map, and/or
matched against contacts extracted from a contact map.
Attributes
----------
hierarchy : :obj:`~conkit.core.contactmap.ContactMap`
The default contact map hierarchy
other : :obj:`~conkit.core.contactmap.ContactMap`
The second contact map hierarchy
reference : :obj:`~conkit.core.contactmap.ContactMap`
The reference contact map hierarchy
altloc : bool
Use the :attr:`~conkit.core.contact.Contact.res_altloc` positions [default: False]
use_conf : bool
The marker size will correspond to the raw score [default: False]
Examples
--------
>>> import conkit
>>> cmap = conkit.io.read('toxd/toxd.mat', 'ccmpred').top_map
>>> conkit.plot.ContactMapFigure(cmap)
"""
def __init__(self, hierarchy, other=None, reference=None, altloc=False, use_conf=False, lim=None, **kwargs):
"""A new contact map plot
Parameters
----------
hierarchy : :obj:`~conkit.core.contactmap.ContactMap`
The default contact map hierarchy
other : :obj:`~conkit.core.contactmap.ContactMap`, optional
The second contact map hierarchy
reference : :obj:`~conkit.core.contactmap.ContactMap`, optional
The reference contact map hierarchy
altloc : bool, optional
Use the :attr:`~conkit.core.contact.Contact.res_altloc` positions [default: False]
use_conf : bool, optional
The marker size will correspond to the raw score [default: False]
lim : tuple, list, optional
The [min, max] residue numbers to show
**kwargs
General :obj:`~conkit.plot.figure.Figure` keyword arguments
"""
super(ContactMapFigure, self).__init__(**kwargs)
self._hierarchy = None
self._other = None
self._reference = None
self._lim = None
self.altloc = altloc
self.use_conf = use_conf
self.hierarchy = hierarchy
if other:
self.other = other
if reference:
self.reference = reference
if lim:
self.lim = lim
self.draw()
def __repr__(self):
return self.__class__.__name__
@property
def hierarchy(self):
return self._hierarchy
@hierarchy.setter
def hierarchy(self, hierarchy):
if hierarchy and _isinstance(hierarchy, "ContactMap"):
self._hierarchy = hierarchy
else:
raise TypeError("Invalid hierarchy type: %s" % hierarchy.__class__.__name__)
@property
def other(self):
return self._other
@other.setter
def other(self, hierarchy):
if hierarchy and _isinstance(hierarchy, "ContactMap"):
self._other = hierarchy
else:
raise TypeError("Invalid hierarchy type: %s" % hierarchy.__class__.__name__)
@property
def reference(self):
return self._reference
@reference.setter
def reference(self, hierarchy):
if hierarchy and _isinstance(hierarchy, "ContactMap"):
self._reference = hierarchy
else:
raise TypeError("Invalid hierarchy type: %s" % hierarchy.__class__.__name__)
@property
def lim(self):
return self._lim
@lim.setter
def lim(self, lim):
if isinstance(lim, (list, tuple)) and len(lim) == 2:
self._lim = lim
elif isinstance(lim, (list, tuple)):
raise ValueError("A list with 2 entries is required!")
else:
raise TypeError("A list with [min, max] limits is required!")
[docs] def draw(self):
if self._reference:
if self.altloc:
reference_data = np.array(self._reference.as_list(altloc=True))
else:
reference_data = np.array(self._reference.as_list())
reference_colors = [ColorDefinitions.STRUCTURAL for _ in np.arange(reference_data.shape[0])]
else:
reference_data = np.empty((0, 2))
reference_colors = []
self_data = np.array([c for c in self._hierarchy.as_list() if all(ci != Gap.IDENTIFIER for ci in c)])
self_colors = ContactMapFigure._determine_color(self._hierarchy)
self_rawsc = np.array(
[c.raw_score for c in self._hierarchy if all(ci != Gap.IDENTIFIER for ci in [c.res1_seq, c.res2_seq])]
)
if self._other:
other_data = np.array([c for c in self._other.as_list() if any(ci != Gap.IDENTIFIER for ci in c)])
other_colors = ContactMapFigure._determine_color(self._other)
other_rawsc = np.array(
[c.raw_score for c in self._other if all(ci != Gap.IDENTIFIER for ci in [c.res1_seq, c.res2_seq])]
)
else:
other_data = self_data
other_colors = self_colors
other_rawsc = self_rawsc
if self.use_conf:
self_radius = normalize(self_rawsc, vmin=0.2, vmax=0.48)
other_radius = normalize(other_rawsc, vmin=0.2, vmax=0.48)
else:
self_radius = other_radius = 0.48
self._patch_scatter(
reference_data[:, 0], reference_data[:, 1], symbol="o", facecolor=reference_colors, radius=0.5, linewidth=0
)
self._patch_scatter(
reference_data[:, 1], reference_data[:, 0], symbol="o", facecolor=reference_colors, radius=0.5, linewidth=0
)
self._patch_scatter(
self_data[:, 1], self_data[:, 0], symbol="o", facecolor=self_colors, radius=self_radius, linewidth=0
)
self._patch_scatter(
other_data[:, 0], other_data[:, 1], symbol="o", facecolor=other_colors, radius=other_radius, linewidth=0
)
if self.lim:
min_max_data = np.arange(self.lim[0], self.lim[1] + 1)
self.ax.set_xlim(self.lim[0] - 0.5, self.lim[1] + 0.5)
self.ax.set_ylim(self.lim[0] - 0.5, self.lim[1] + 0.5)
else:
min_max_data = np.append(self_data[:, 0], self_data[:, 1])
if self._reference:
min_max_data = np.append(min_max_data, reference_data[:, 0])
min_max_data = np.append(min_max_data, reference_data[:, 1])
if self._other:
min_max_data = np.append(min_max_data, other_data[:, 0])
min_max_data = np.append(min_max_data, other_data[:, 1])
min_v, max_v = min_max_data.min(), min_max_data.max()
if abs(max_v - min_v) < 10:
min_v = max(0, (max_v + min_v) // 2 - 5)
max_v = min_v + 10
self.ax.set_xlim(min_v - 0.5, max_v + 0.5)
self.ax.set_ylim(min_v - 0.5, max_v + 0.5)
gap = 10 * (max_v - min_v) // 100
tick_range = np.arange(min_v, max_v + 1, gap, dtype=np.int64)
self.ax.set_xticks(tick_range)
self.ax.set_yticks(tick_range)
self.ax.set_xlabel("Residue number")
self.ax.set_ylabel("Residue number")
line2d_kws = dict(marker="o", linestyle="")
pseudo_data = [[0, 1], [0, 0]]
if self._reference:
tp_artist = plt.Line2D(*pseudo_data, color=ColorDefinitions.MATCH, label="Match", **line2d_kws)
fp_artist = plt.Line2D(*pseudo_data, color=ColorDefinitions.MISMATCH, label="Mismatch", **line2d_kws)
rf_artist = plt.Line2D(*pseudo_data, color=ColorDefinitions.STRUCTURAL, label="Structural", **line2d_kws)
artists = [tp_artist, fp_artist, rf_artist]
else:
nt_artist = plt.Line2D(*pseudo_data, color=ColorDefinitions.GENERAL, label="Contact", **line2d_kws)
artists = [nt_artist]
if self.legend:
self.ax.legend(
handles=artists,
numpoints=1,
fontsize=10,
bbox_to_anchor=(0.0, 1.02, 1.0, 0.102),
loc=3,
ncol=3,
mode="expand",
borderaxespad=0.0,
)
# TODO: deprecate this in 0.14
if self._file_name:
self.savefig(self._file_name, dpi=self._dpi)
@staticmethod
def _determine_color(h):
"""Determine the color of the contacts in order"""
def color_selector(contact):
if contact.true_positive:
return ColorDefinitions.MATCH
elif contact.false_positive:
return ColorDefinitions.MISMATCH
else:
return ColorDefinitions.GENERAL
return [color_selector(contact) for contact in h if Gap.IDENTIFIER not in (contact.res1_seq, contact.res2_seq)]