Source code for rnaglib.drawing.rna_draw

import os
import sys

import networkx as nx
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns

from rnaglib.utils.graph_io import load_json
from rnaglib.drawing.rna_layout import circular_layout
from distutils.spawn import find_executable

use_tex = False
if find_executable('latex'):
    use_tex = True
    print("No LaTex installation was found, using a fallback drawing system.")

if use_tex:
    matplotlib.rcParams['text.usetex'] = True
    params = {'text.latex.preamble': r'\usepackage{fdsymbol}\usepackage{xspace}'}
    plt.rc('font', family='serif')
    labels = {
        'cW': r"$\medblackcircle$\xspace",
        'cS': r"$\medblacktriangleright$\xspace",
        'cH': r"$\medblacksquare$\xspace",
        'tW': r"$\medcircle$\xspace",
        'tS': r"$\medtriangleright$\xspace",
        'tH': r"$\medsquare$\xspace"
    labels = {
        'cW': r"$\oplus\ $",
        'cS': r"$\blacktriangleright\ $",
        'cH': r"$\blacksquare\ $",
        'tW': r"$\bigcirc\ $",
        'tS': r"$\triangleright\ $",
        'tH': r"$\boxdot\ $",

make_label = lambda s: labels[s[:2]] + labels[s[0::2]] if len(set(s[1:])) == 2 else labels[s[:2]]

NT_COLORS = {'A': 'blue', 'U': 'green', 'C': 'red', 'G': 'yellow', 'a': 'blue', 'u': 'green', 'c': 'red', 'g': 'yellow'}

[docs]def process_axis(axis, g, subtitle=None, highlight_edges=None, node_color=None, node_labels=None, node_ids=False, layout='spring', label='LW'): """ Draw a graph on a given axis. :param axis: matplotlib axis to draw on :param g: networkx graph to draw :param subtitle: string to use as a subtitle on this axis :param highlight_edges: A list of edges to highlight on the drawing :param node_color: :param node_labels: :param node_ids: :param label: :return: """ if layout == 'spring': pos = nx.spring_layout(g) else: pos = circular_layout(g) if not node_color is None: nodes = nx.draw_networkx_nodes(g, pos, node_size=50, node_color=node_color, linewidths=1, ax=axis) else: nt_color = [] for node, d in g.nodes(data=True): try: nt_color.append(NT_COLORS[d['nt_code']]) except: nt_color.append('grey') nodes = nx.draw_networkx_nodes(g, pos, node_size=50, node_color=nt_color, linewidths=1, ax=axis) if node_ids: node_labels = {n: str(n).replace("_", "-") for n in g.nodes()} nx.draw_networkx_labels(g, pos, node_labels, font_color='black', ax=axis) if not node_labels is None: nx.draw_networkx_labels(g, pos, node_labels, font_color='black', ax=axis) nodes.set_edgecolor('black') edge_labels = {} for n1, n2, d in g.edges(data=True): try: symbol = make_label(d[label]) edge_labels[(n1, n2)] = symbol except: if d[label] == 'B53' or d[label] == 'B35': edge_labels[(n1, n2)] = '' else: edge_labels[(n1, n2)] = r"{0}".format(d[label]) continue non_bb_edges = [(n1, n2) for n1, n2, d in g.edges(data=True) if d[label][0] != 'B'] # bb_edges = [(n1, n2) for n1, n2, d in g.edges(data=True) if d[label][0] == 'B'] bb_edges = [(n1, n2) for n1, n2, d in g.edges(data=True) if d[label] == 'B53'] nx.draw_networkx_edges(g, pos, edge_color="red", edgelist=non_bb_edges, ax=axis) # nx.draw_networkx_edges(g, pos, edge_color="red", connectionstyle="arc3,rad=0.1", edgelist=non_bb_edges, ax=axis) nx.draw_networkx_edges(g, pos, edgelist=bb_edges, width=1, ax=axis) if not highlight_edges is None: nx.draw_networkx_edges(g, pos, edgelist=highlight_edges, edge_color='y', width=8, alpha=0.5, ax=axis) nx.draw_networkx_edge_labels(g, pos, font_size=10, edge_labels=edge_labels, ax=axis) axis.set_axis_off() if not subtitle is None: axis.set_title(subtitle)
[docs]def rna_draw(g, title="", node_ids=False, highlight_edges=None, node_labels=None, node_colors=None, num_clusters=None, pos=None, pos_offset=(0, 0), scale=1, ax=None, show=False, alpha=1, save=False, node_size=250, fontsize=12, format='pdf', seed=None, layout='circular'): """ Draw an RNA with the edge labels used by Leontis Westhof :param nx_g: :param title: :param highlight_edges: :param node_colors: :param num_clusters: :return: """ if ax is None: fig, ax = plt.subplots(1, 1) pos = circular_layout(g) process_axis(ax, g, subtitle=title, highlight_edges=highlight_edges, node_color=node_colors, node_labels=node_labels, layout=layout) if save: plt.savefig(save, format=format) plt.clf() if show: return ax
# plt.clf()
[docs]def rna_draw_pair(graphs, subtitles=None, highlight_edges=None, node_colors=None, save=None, show=False, node_ids=False): """ Plot a line of plots of graphs along with a value for each graph. Useful for graph comparison vizualisation :param graphs: iterable nx graphs :param estimated_value: iterable of values of comparison (optional) :param iihighlight_edges: :param node_colors: iterable of node colors :return: """ fig, ax = plt.subplots(1, len(graphs), num=1) for i, g in enumerate(graphs): subtitle, node_color = (None, None) if not subtitles is None: subtitle = subtitles[i] if not node_colors is None: node_color = node_colors[i] process_axis(ax[i], g, subtitle=subtitle, highlight_edges=highlight_edges, node_color=node_color) plt.axis('off') plt.tight_layout() if save: plt.savefig(save, format='pdf') if show:
[docs]def rna_draw_grid(graphs, subtitles=None, highlight_edges=None, node_colors=None, row_labels=None, save=None, show=False, format='png', grid_shape=None): """ Plot a line of plots of graphs along with a value for each graph. Useful for graph comparison vizualisation :param graphs: list of lists containing nx graphs all lists must have the same dimension along axis 1. To skip a cell, add a None instead of graph. :param estimated_value: iterable of values of comparison (optional) :param highlight_edges: :param node_colors: iterable of node colors :return: """ if grid_shape is None: assert len(set(map(len, graphs))) == 1, "All rows must have the same number of entries." if not subtitles is None: assert len(set(map(len, subtitles))) == 1, "All rows must have the same number of entries." N = len(graphs) M = len(graphs[0]) fig, ax = plt.subplots(N, M, num=1) for i, gs in enumerate(graphs): for j, g in enumerate(gs): process_axis(ax, g, subtitle=subtitles[i], highlight_edges=highlight_edges, node_color=node_colors) else: m, n = grid_shape assert m * n == len(graphs) fig, axes = plt.subplots(nrows=m, ncols=n) for i in range(len(graphs)): k, l = i // n, i % n process_axis(axes[k, l], graphs[i], subtitle='', highlight_edges=highlight_edges, node_color='grey') if not row_labels is None: for a, row in zip(ax[:, 0], row_labels): a.set_ylabel(row, rotation=0) plt.axis('off') if save: plt.savefig(save, format=save_format) if show:
if __name__ == "__main__": G = load_json("data/examples/4nlf.json") rna_draw(G, show=True) # for f in os.listdir("data/all_graphs_chops"): # G = nx.read_gpickle(os.path.join("data/all_graphs_chops", f)) # print("HI") # print(f) # rna_draw(G, show=True, format="pdf") pass