plot_weights()

Complexity

Conditions

7

Size

Total Lines

75

Duplication

Lines	0
Ratio	0 %

Code Coverage

Tests	1
CRAP Score	51.5414

Importance

Changes	1
Bugs	0	Features	1

1 Method

Rating	Name	Duplication	Size	Complexity
A	gaussian()	0	4	1

#! /usr/bin/env python
#
# Copyright (C) 2015-2016 Rich Lewis <rl403@cam.ac.uk>
# License: 3-clause BSD

"""
## skchem.vis.atom

Module for atom contribution visualization.
"""

from rdkit.Chem.Draw import MolToImage, DrawingOptions

The import rdkit.Chem.Draw could not be resolved.

import numpy as np

The import numpy could not be resolved.

from matplotlib import pyplot as plt

The import matplotlib could not be resolved.

def plot_weights(mol, weights, quality=1, l=0.4, step=50, levels=20,

The name l does not conform to the argument naming conventions ([a-z_][a-z0-9_]{2,30}$).

The name ax does not conform to the argument naming conventions ([a-z_][a-z0-9_]{2,30}$).

Too many arguments (9/5)

This function exceeds the maximum number of variables (30/15).

The argument step seems to be unused.

                 contour_opacity=0.5, cmap='RdBu', ax=None, **kwargs):
    """ Plot weights as a sum of gaussians across a structure image.

    Args:
        mol (skchem.Mol):
            Molecule to visualize weights for.
        weights (iterable<float>):
            Array of weights in atom index order.
        l (float):
            Lengthscale of gaussians to visualize as a multiple of bond length.
        step (int):
            Size of grid edge to calculate the gaussians.
        levels (int):
            Number of contours to plot.
        contour_opacity (float):
            Alpha applied to the contour layer.
        ax (plt.axis):
            Axis to apply the plot to. Defaults to current axis.
        cmap (plt.cm):
            Colormap to use for the contour.
        **kwargs:
            Passed to contourf function.

    Returns:
        matplotlib.AxesSubplot: The plot.
    """

    if not ax:
        ax = plt.gca()
    ax.grid('off')
    ax.axis('off')

    opts = DrawingOptions()
    opts.dotsPerAngstrom *= quality
    opts.atomLabelFontSize *= quality
    opts.bondLineWidth *= quality

    size = 300 * quality

    img, canvas, drawer = MolToImage(mol, size=(size, size), options=opts,
                                     returnCanvas=True)
    canvas.flush()
    coords = [[i / size, 1 - j / size]
              for k, (i, j) in list(drawer.atomPs.values())[0].items()]

The variable k seems to be unused.

    coords = np.array(coords)

    b = mol.bonds[0]

The name b does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

    begin, end = b.GetBeginAtom().GetIdx(), b.GetEndAtom().GetIdx()
    length = np.linalg.norm(coords[end] - coords[begin])

    x = np.linspace(0, 1, 500)

The name x does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

    y = np.linspace(0, 1, 500)

The name y does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

    x, y = np.meshgrid(x, y)

The name x does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

The name y does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

    def gaussian(x, y, mu=np.zeros(2), sigma=np.identity(2), size=50):

The name x does not conform to the argument naming conventions ([a-z_][a-z0-9_]{2,30}$).

The name y does not conform to the argument naming conventions ([a-z_][a-z0-9_]{2,30}$).

The name mu does not conform to the argument naming conventions ([a-z_][a-z0-9_]{2,30}$).

This function should have a docstring.

The argument size seems to be unused.

        return (1 / (2 * np.pi * sigma[0, 0] * sigma[1, 1]) *
                np.exp(-((x - mu[0]) ** 2 / (2 * sigma[0, 0] ** 2) +
                         (y - mu[1]) ** 2 / (2 * sigma[1, 1] ** 2))))

    if not np.max(weights) == np.min(weights) == 0:
        z = sum([w * gaussian(x, y, mu, sigma=l * length * np.identity(2))

The name z does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

                 for mu, w in zip(coords, weights)])
        v = np.max((np.abs(z.min()), np.abs(z.max())))

The name v does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

    else:
        z = np.zeros(x.shape)

The name z does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

        v = 1

The name v does not conform to the variable naming conventions ([a-z_][a-z0-9_]{2,30}$).

    if z.min() >= 0:
        levels = int(levels/2)
    ax.contourf(x, y, z, levels, alpha=contour_opacity,
                extent=(0, 1, 0, 1), vmin=-v, vmax=v, cmap=cmap, **kwargs)

    ax.imshow(img, extent=(0, 1, 0, 1))
    return ax