Visualizer

`draw_molecule`	Draw a molecule using RDKit
`draw_alignment`	Draw the alignment of multiple spectrums
`draw_frag_of_molecule`	draws a fragment of the molecule.
`draw_modifications`	Draw the modifications from molecule 1 to molecule 2
`draw_molecule_heatmap`	Draw a molecule and color the atoms based on the scores
`draw_spectrum`	Draw a spectrum

More information on the features provided here are available at

rdkit: http://www.rdkit.org/ matplotlib: http://matplotlib.org/

GNPS Utils - Visualizer Module

This module provides functionality to visualize data from GNPS.

Author: Shahneh

modifinder.utilities.visualizer.draw_alignment(spectrums, matches=None, output_type='png', normalize_peaks=False, size=None, dpi=300, draw_mapping_lines=True, ppm=40, x_lim=None, **kwargs)[source]

Draw the alignment of multiple spectrums

Parameters:

spectrums (list of SpectrumTuple or list of list of tuples (mz, intensity)) – list of spectrums to draw
matches (list of list of tuples or list of tuples, optional (default=None)) – matching between the spectrums
output_type (str, optional (default='png')) – type of output (png or svg)
normalize_peaks (bool, optional (default=False)) – normalize the peaks or not
size (tuple, optional (default=None)) – size of the figure
dpi (int, optional (default=300)) – dpi of the stored image
draw_mapping_lines (bool, optional (default=True)) – draw the mapping lines
ppm (float, optional (default=40)) – ppm value for the alignment
x_lim (tuple, optional (default=None)) – x limit of the figure
kwargs (dict) – additional arguments for drawing the spectrum in matplotlib

Returns:

img

Return type:

numpy array or str

Examples

import modifinder.utilities.visualizer as mf_vis
from matplotlib import pyplot as plt
import numpy as np
peaks1 = list(zip([100, 200, 270, 400, 450], [0.1, 0.2, 0.5, 0.4, 0.3]))
peaks2 = list(zip([100, 230, 350, 360, 430], [0.1, 0.3, 0.2, 0.4, 0.5]))
peaks3 = list(zip([120, 230, 300, 380, 550], [0.1, 0.2, 0.5, 0.4, 0.3]))
matches = [[(0, 0), (1, 1), (3, 4)], [(0, 0), (1, 1), (3, 3)]]
img = mf_vis.draw_alignment([peaks1, peaks2, peaks3], matches=matches,
                            output_type='png',
                            normalize_peaks=True,
                            x_lim=(0, 550))
plt.imshow(img)
plt.axis('off')
plt.show()

modifinder.utilities.visualizer.draw_frag_of_molecule(mol, fragment, output_type='png', **kwargs)[source]

draws a fragment of the molecule. The fragment is represented by a binary string where 1 indicates the presence of the atom and 0 indicates the absence.

Parameters:

mol (rdkit molecule) – Molecule to draw the fragment for
fragment (int or list) – fragment represented in base 10 where in the binary representation 1 indicates the presence of the atom and 0 indicates the absence, or a list of atom indices
output_type (str, optional (default='png')) – type of output (png or svg)
kwargs (dict) – additional arguments for drawing the molecule in rdkit

Returns:

img

Return type:

numpy array or str

Examples

import modifinder.utilities.visualizer as mf_vis
from matplotlib import pyplot as plt
from rdkit import Chem
mol = Chem.MolFromSmiles('CN1C=NC2=C1C(=O)N(C(=O)N2C)C')
def mol_with_atom_index(mol):
    for atom in mol.GetAtoms():
        atom.SetAtomMapNum(atom.GetIdx())
    return mol
mol = mol_with_atom_index(mol)
fragment = int("110111", 2) # Convert binary to decimal
img = mf_vis.draw_frag_of_molecule(mol, fragment, output_type='png')
plt.imshow(img)
plt.axis('off')
plt.show()

modifinder.utilities.visualizer.draw_modifications(mol1, mol2, output_type='png', show_legend=True, legend_font=15, legend_position=None, highlight_common=True, highlight_added=True, highlight_removed=True, modification_only=False, **kwargs)[source]

Draw the modifications from molecule 1 to molecule 2

Parameters:

mol1 (rdkit molecule, str) – rdkit molecule or str for SMILES or InChI or GNPS identifier (USI or Accession)
mol2 (rdkit molecule) – rdkit molecule or str for SMILES or InChI or GNPS identifier (USI or Accession)
output_type (str, optional (default='png')) – type of output (png or svg)
show_legend (bool, optional (default=True)) – show the legend or not
legend_font (int, optional (default=15)) – font size of the legend
legend_position (tuple, optional (default=None)) – position of the legend
highlight_common (bool, optional (default=True)) – highlight the common atoms
highlight_added (bool, optional (default=True)) – highlight the added atoms
highlight_removed (bool, optional (default=True)) – highlight the removed atoms
modification_only (bool, optional (default=False)) – only highlight the modification edges, if highlight_removed or highlight_added is False, this will only show the enabled ones

Returns:

img – image of the modification

Return type:

numpy array or str

Examples

import modifinder.utilities.visualizer as mf_vis
from matplotlib import pyplot as plt
from rdkit import Chem

smiles1, smiles2 = 'N[C@@H](CCC(=O)N[C@@H](CS)C(=O)NCC(O)=O)C(O)=O', 'CCCCCCSCC(CNCC(=O)O)NC(=O)CCC(C(=O)O)N'
mol1 = mf_vis.draw_molecule(smiles1, label="mol1")
mol2 = mf_vis.draw_molecule(smiles2, label="mol2")
modification = mf_vis.draw_modifications(smiles1, smiles2, label="modifications")
fig, ax = plt.subplots(1, 3, figsize=(15, 5))
ax[0].imshow(mol1)
ax[1].imshow(mol2)
ax[2].imshow(modification)
for a in ax:
    a.axis('off')
plt.show()

modifinder.utilities.visualizer.draw_molecule(mol, output_type='png', font_size=None, label=None, label_font_size=20, label_color=(0, 0, 0), label_position='top', **kwargs)[source]

Draw a molecule using RDKit

Parameters:

mol (rdkit molecule or str) – rdkit molecule or str for SMILES or InChI or GNPS identifier (USI or Accession)
output_type (str) – type of output (png or svg)
font_size (int, optional (default=None)) – font size for the labels
label (str, optional (default=None)) – label for the molecule
label_font_size (int, optional (default=20)) – font size for the label
label_color (tuple, optional (default=(0,0,0))) – color of the label
label_position (str, optional (default='top')) – position of the label (top or bottom)
kwargs (dict) – additional arguments for drawing the molecule in rdkit like highlightAtoms, highlightAtomColors, highlightBonds, highlightBondColors, highlightAtomRadii, etc.

Returns:

img – image of the molecule

Return type:

numpy array or str

Examples

import modifinder.utilities.visualizer as mf_vis
from matplotlib import pyplot as plt

img = mf_vis.draw_molecule('CN1C=NC2=C1C(=O)N(C(=O)N2C)C', output_type='png', label="Caffeine")
plt.imshow(img)
plt.axis('off')
plt.show()

import modifinder.utilities.visualizer as mf_vis
from matplotlib import pyplot as plt
from rdkit import Chem

def mol_with_atom_index(mol):
    for atom in mol.GetAtoms():
        atom.SetAtomMapNum(atom.GetIdx())
    return mol
mol = Chem.MolFromSmiles('CN1C=NC2=C1C(=O)N(C(=O)N2C)C')
mol = mol_with_atom_index(mol)
highlightAtoms = {1, 3, 11, 8}
img = mf_vis.draw_molecule(mol, output_type='png', label="Caffeine", highlightAtoms=highlightAtoms)
plt.imshow(img)
plt.axis('off')
plt.show()

modifinder.utilities.visualizer.draw_molecule_heatmap(mol, scores, output_type='png', show_labels=False, shrink_labels=False, annotation_scale=1, show_legend=True, legend_width=50, legend_font=40, **kwargs)[source]

Draw a molecule and color the atoms based on the scores

Parameters:

mol (rdkit molecule) – Molecule to Draw the heatmap for
scores (list) – list of scores for each atom (the order should be the same as the order of atoms in the molecule)
output_type (str, optional (default='png')) – type of output (png or svg)
show_labels (bool, optional (default=False)) – add labels to the atoms
shrink_labels (bool, optional (default=False)) – shrink the labels to more compact form
annotation_scale (float, optional (default=1)) – size of the labels (font size)
show_legend (bool, optional (default=True)) – show the legend or not
legend_width (int, optional (default=50)) – width of the legend in pixels
legend_font (int, optional (default=40)) – font size of the legend

Returns:

img

Return type:

numpy array or str

Examples

import modifinder.utilities.visualizer as mf_vis
from matplotlib import pyplot as plt
import numpy as np
mol = Chem.MolFromSmiles('CN1C=NC2=C1C(=O)N(C(=O)N2C)C')
scores = np.random.rand(mol.GetNumAtoms())
img = mf_vis.draw_molecule_heatmap(mol, scores, label="Caffeine", show_labels=True, legend_font=20)
plt.imshow(img)
plt.axis('off')
plt.show()

modifinder.utilities.visualizer.draw_spectrum(spectrum, output_type='png', normalize_peaks=False, colors: dict = {}, flipped=False, size=None, show_x_label=False, show_y_label=False, font_size=None, bar_width=3, x_lim=None, dpi=300, **kwargs)[source]

Draw a spectrum

Parameters:

spectrum (Spectrum or list of tuples or USI or Accession) – Spectrum to draw
output_type (str, optional (default='png')) – type of output (png or svg)
normalize_peaks (bool, optional (default=False)) – normalize the peaks or not
colors (dict, optional (default={})) – dictionary of colors for the peaks, keys are the indices of the peaks, if value is a list, the first value is the color of top half and the second value is the color of the bottom half.
flipped (bool, optional (default=False)) – flip the spectrum or not
size (tuple, optional (default=None)) – size of the figure
show_x_label (bool, optional (default=False)) – show x label or not
show_y_label (bool, optional (default=False)) – show y label or not
font_size (int, optional (default=None)) – font size of the labels
bar_width (int, optional (default=3)) – width of the spectrum bars
x_lim (tuple, optional (default=None)) – x limit of the figure
dpi (int, optional (default=300)) – dpi of the stored image
kwargs (dict) – additional arguments for drawing the spectrum in matplotlib

Returns:

img

Return type:

numpy array or str

Examples

import modifinder.utilities.visualizer as mf_vis
from matplotlib import pyplot as plt
import numpy as np
mz = [100, 200, 270, 400, 450]
intensity = [0.1, 0.2, 0.5, 0.4, 0.3]
colors = {
    0: 'red',
    1: ['blue', 'green'],
    3: '#FFA500',
    4: (0.9,0.9,0.2)
}
img = mf_vis.draw_spectrum(list(zip(mz, intensity)), output_type='png', show_x_label=True, show_y_label=True, colors=colors)
plt.imshow(img)
plt.axis('off')
plt.show()

modifinder.utilities.visualizer.return_public_functions()[source]: Return the public functions of the module