def plot(part):
n = makenode(part)
proc = n.graph()
G = nx.Graph()
G.add_edges_from(proc)
# TODO: can this be done without reading and writing a file?
nx.write_edgelist(G, path="grid.edgelist", delimiter=":")
H = nx.read_edgelist(path="grid.edgelist", delimiter=":")
os.unlink("grid.edgelist")
layout = l.kamada_kawai_layout(G, pos=l.shell_layout(G))
nx.draw(
H,
pos=layout,
edge_color="#777777",
node_color="#ffffff",
with_labels=True,
font_family="Arial",
font_size=9,
label=part,
)
#plt.show()
if not os.path.isdir('output'): os.makedirs('output')
path = os.path.join('output', part + '.svg')
plt.savefig(path, format="svg")
plt.close()
def calculate2d(self, force=False, scale=1):
"""
recalculate 2d coordinates. currently rings can be calculated badly.
:param scale: rescale calculated positions.
:param force: ignore existing coordinates of atoms
"""
dist = {}
# length forces
for n, m_bond in self._adj.items():
dist[n] = {}
for m in m_bond:
dist[n][m] = .825
# angle forces
for n, m_bond in self._adj.items():
if len(m_bond) == 2: # single-single or single-double bonds has angle = 120, other 180
(m1, b1), (m2, b2) = m_bond.items()
dist[m1][m2] = dist[m2][m1] = 1.43 if b1.order + b2.order in (2, 3) else 1.7 # +.05
elif len(m_bond) == 3:
m1, m2, m3 = m_bond
dist[m1][m2] = dist[m1][m3] = dist[m2][m3] = dist[m3][m2] = dist[m2][m1] = dist[m3][m1] = 1.43
elif len(m_bond) == 4:
# 1
#
# 2 X 4
#
# 3
m1, m2, m3, m4 = m_bond
dist[m1][m2] = dist[m1][m4] = dist[m2][m1] = dist[m2][m3] = 1.17
dist[m3][m2] = dist[m3][m4] = dist[m4][m1] = dist[m4][m3] = 1.17
dist[m1][m3] = dist[m3][m1] = dist[m2][m4] = dist[m4][m2] = 1.7 # +.05
# cycle forces
for r in self.sssr:
if len(r) == 6:
# 6
#
# 1 5
#
# 2 4
#
# 3
m1, m2, m3, m4, m5, m6 = r
dist[m1][m4] = dist[m4][m1] = dist[m2][m5] = dist[m5][m2] = dist[m3][m6] = dist[m6][m3] = 1.7 # +.05
if force:
pos = None
else:
pos = {n: (atom.x or uniform(0, .01), atom.y or uniform(0, .01)) for n, atom in self.atoms()}
for n, xy in kamada_kawai_layout(self, dist=dict(dist), pos=pos, scale=scale).items():
atom = self._node[n]
atom.x, atom.y = xy
self.flush_cache()
def draw_kamada_kawai(G, **kwargs):
"""Draw the graph G with a Kamada-Kawai force-directed layout.
Parameters
----------
G : graph
A networkx graph
kwargs : optional keywords
See networkx.draw_networkx() for a description of optional keywords,
with the exception of the pos parameter which is not used by this
function.
"""
draw(G, kamada_kawai_layout(G), **kwargs)
def draw_kamada_kawai(G, **kwargs):
"""Draw the graph G with a Kamada-Kawai force-directed layout.
Parameters
----------
G : graph
A networkx graph
kwargs : optional keywords
See networkx.draw_networkx() for a description of optional keywords,
with the exception of the pos parameter which is not used by this
function.
"""
draw(G, kamada_kawai_layout(G), **kwargs)
# %%
import networkx as nx
# from networkx.algorithms import centrality
from networkx.readwrite import gexf
import pandas as pd
import matplotlib.pyplot as plt
from networkx.drawing import layout
## https://networkx.github.io/documentation/networkx-1.10/reference/generated/networkx.drawing.nx_agraph.graphviz_layout.html
# %%
print('start')
G = gexf.read_gexf('3mj/subgraph--1-start.gexf')
print('generate layout')
sp = layout.kamada_kawai_layout(G)
degrees = pd.DataFrame(dict(G.degree).items(), columns=['tag', 'degree'])
print(nx.__version__)
print('before')
print(nx.info(G))
nodes_zero_degree = (degrees.query('degree == 0')['tag'].to_list())
G.remove_nodes_from(nodes_zero_degree)
print('after')
print(nx.info(G))
# %%
df_decompose = pd.read_csv('3mj/decomposed_3mj.csv')[[
'iteration', 'tag', 'filename'
]]
def draw_graph(G, ax=None, circular=True):
if ax is None:
_, ax = plt.subplots(figsize=(9, 9))
# Compute the position of the vertices
if circular:
pos = layout.circular_layout(G)
else:
pos = layout.kamada_kawai_layout(G, weight='weight')
# Get the node data to draw nodes on
node_sizes = []
node_labels = {}
label_colors = {}
node_colors = []
linewidths = []
edgecolors = []
for v, data in G.nodes(data=True):
node_sizes.append(data.get('size', 1200))
node_labels[v] = data.get('label', LOCATION_CODES[v])
node_color = data.get('color', LOCATION_COLORS[v])
node_colors.append(node_color)
label_colors[v] = font_color(node_color)
if data.get('halo', False):
linewidths.append(8.0)
edgecolors.append(data.get('halo_color', '#F4D03F'))
else:
linewidths.append(1.0)
edgecolors.append("#666666")
# Draw nodes with above properties
nx.draw_networkx_nodes(
G,
pos=pos,
ax=ax,
node_size=node_sizes,
node_color=node_colors,
linewidths=linewidths,
edgecolors=edgecolors,
)
# Draw node labels by light and dark color
for color in set(label_colors.values()):
labels = {
v: node_labels[v]
for v, c in label_colors.items() if c == color
}
nx.draw_networkx_labels(
G,
pos=pos,
labels=labels,
font_color=color,
font_size=11,
font_family="serif",
)
# Get edge properties to draw edges on
edge_widths = []
edge_colors = []
for src, dst, data in G.edges(data=True):
edge_widths.append(data.get('size', 1.0))
edge_colors.append(data.get('color', 'k'))
nx.draw_networkx_edges(G,
pos=pos,
ax=ax,
width=edge_widths,
edge_color=edge_colors)
# Remove grid and axes
ax.grid(False)
ax.axis('off')
return ax
