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"""Internal utility functions"""
__author__ = "Felix Simkovic"
__date__ = "16 Feb 2017"
__version__ = "0.1"
import numpy as np
from conkit.core.contact import Contact
from conkit.core.contactmap import ContactMap
from conkit.core.contactfile import ContactFile
from conkit.core.sequence import Sequence
from conkit.core.sequencefile import SequenceFile
from conkit.misc import deprecate
HierarchyIndex = {
"Contact": Contact,
"ContactMap": ContactMap,
"ContactFile": ContactFile,
"Sequence": Sequence,
"SequenceFile": SequenceFile,
}
[docs]class ColorDefinitions(object):
"""A class storing all color definitions for the various plots
for fast and easy handling
"""
GENERAL = "#000000"
MATCH = "#0F0B2C"
MISMATCH = "#DC4869"
STRUCTURAL = "#D8D6D6"
L5CUTOFF = "#3F4587"
L20CUTOFF = "#B5DD2B"
PRECISION50 = L5CUTOFF
FACTOR1 = L20CUTOFF
AA_ENCODING = {
"A": "#882D17",
"C": "#F3C300",
"D": "#875692",
"E": "#F38400",
"F": "#A1CAF1",
"G": "#BE0032",
"H": "#C2B280",
"I": "#848482",
"K": "#008856",
"L": "#E68FAC",
"M": "#0067A5",
"N": "#F99379",
"P": "#604E97",
"Q": "#F6A600",
"R": "#B3446C",
"S": "#DCD300",
"T": "#8DB600",
"V": "#654522",
"W": "#E25822",
"Y": "#2B3D26",
"X": "#000000",
}
[docs]def find_minima(data, order=1):
"""Find the minima in a 1-D list
Parameters
----------
data : list, tuple
A list of values
order : int, optional
The order, i.e. number of points next to point to consider
Returns
-------
list
A list of indices for minima
Warning
-------
For multi-dimensional problems, see :func:`~scipy.signal.argrelmin`.
Raises
------
:exc:`ValueError`
Order needs to be >= 1!
:exc:`ValueError`
More than two elements required!
"""
if order < 1:
raise ValueError("Order needs to be >= 1!")
data = np.asarray(data)
nelements = data.shape[0]
if nelements < 2:
raise ValueError("More than two elements required!")
results = np.zeros(nelements, dtype=np.bool_)
for i in np.arange(1, nelements - 1):
start = 0 if i - order < 0 else i - order
end = nelements if i + order + 1 > nelements else i + order + 1
results[i] = np.all(data[start:i] > data[i]) and np.all(data[i] < data[i + 1 : end])
return np.where(results)[0].tolist()
[docs]def get_adjusted_aspect(ax, aspect_ratio):
"""Adjust the aspect ratio
Parameters
----------
ax : :obj:`~matplotlib.axes.Axes`
A :obj:`~matplotlib.axes.Axes` instance
aspect_ratio : float
The desired aspect ratio for :obj:`~matplotlib.axes.Axes`
Returns
-------
float
The required aspect ratio to achieve the desired one
Warning
-------
This function only works for non-logarithmic axes.
"""
default_ratio = (ax.get_xlim()[1] - ax.get_xlim()[0]) / (ax.get_ylim()[1] - ax.get_ylim()[0])
return float(default_ratio * aspect_ratio)
@deprecate("0.11", msg="Use get_points_on_circle instead")
def points_on_circle(*args, **kwargs):
return get_points_on_circle(*args, **kwargs)
[docs]def get_points_on_circle(radius, h=0, k=0):
"""Calculate points on a circle with even spacing
Parameters
----------
radius : int
The radius of the circle
h : int, optional
The x coordinate of the origin
k : int, optional
The y coordinate of the origin
Returns
-------
list
The list of coordinates for each point
"""
if radius == 0:
return [[]]
else:
space = 2 * np.pi / radius
coords = np.zeros((radius, 2))
for i in np.arange(radius):
coords[i] = [round(h + radius * np.cos(space * i), 6), round(k + radius * np.sin(space * i), 6)]
return coords.tolist()
[docs]def get_radius_around_circle(p1, p2):
"""Obtain the radius around a given circle
Parameters
----------
p1 : list, tuple
Point 1
p2 : list, tuple
Point 2 adjacent `p1`
Returns
-------
float
The radius for points so p1 and p2 do not intersect
"""
dist = np.linalg.norm(np.array(p1) - np.array(p2))
return dist / 2.0 - dist * 0.1
def _isinstance(hierarchy, hierarchy_type):
"""Confirm the data structure to be a ConKit definition"""
if isinstance(hierarchy_type, str) and hierarchy_type in HierarchyIndex:
return isinstance(hierarchy, HierarchyIndex[hierarchy_type])
else:
return isinstance(hierarchy, hierarchy_type)
