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protograph.py
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protograph.py
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import networkx as nx
import json
import plotly.graph_objects as go
import sys
import numpy as np
import math
try:
from sklearn.manifold import MDS
import scipy
except ImportError:
pass
# load
path = sys.argv[1]
name = path.split('/')[-1]
with open(path, 'r') as f:
data = json.loads(f.read())
G = nx.readwrite.json_graph.node_link_graph(data, directed=True, multigraph=False)
G = nx.OrderedDiGraph(G) # for safety w/ MDS code below
# Parse command line args
focal_nodes = []
depth = None
trawl = lambda _set, member: _set.union(G.successors(member)).union(G.predecessors(member))
args = iter(sys.argv[2:])
for arg in args:
if arg == "--depth":
depth = int(next(args))
elif arg == "--upstream":
trawl = lambda _set, member: _set.union(G.predecessors(member))
elif arg == "--downstream":
trawl = lambda _set, member: _set.union(G.successors(member))
else:
try:
int(arg)
focal_nodes.append(arg)
except ValueError:
print(f"Argument {arg} not recognized!")
sys.exit(1)
if not depth:
depth = 2
# Get subgraph as specified in arguments
subtitle = ""
if len(focal_nodes) > 0:
# filter graph to neighborhood
keepers = set(focal_nodes)
for _ in range(depth):
for k in keepers.copy():
keepers = trawl(keepers, k)
droppers = np.setdiff1d(G.nodes, list(keepers)) # np doesn't like sets...
G.remove_nodes_from(droppers)
#subtitle = f"'{G.nodes[focal_nodes[0]]['text']}'"
# Initial layout
try:
# start with MDS, if scikit available
adj = nx.convert_matrix.to_scipy_sparse_matrix(G)
dist = scipy.sparse.csgraph.dijkstra(adj, directed=False)
nodes = list(G.nodes)
coords = MDS(dissimilarity='precomputed').fit_transform(dist)
pos = {nodes[i]: coords[i] for i in range(len(nodes))}
except (NameError, ValueError):
print("(You may get better graph-drawing results if python lib scikit-learn is available)")
try:
pos = nx.drawing.layout.planar_layout(G)
except nx.exception.NetworkXException:
#pos = nx.drawing.layout.spectral_layout(G)
pos = nx.drawing.layout.kamada_kawai_layout(G)
# Layout
#pos = nx.drawing.layout.spring_layout(G, k=150/math.sqrt(len(G.nodes)), iterations=1000, threshold=1e-3, pos=pos)
# Plotting
def arrow(x0, y0, x1, y1):
vector = np.array((x1-x0, y1-y0))
midpoint = np.array([(x0 + x1)/2, (y1+y0)/2])
scale = .05
orthpoint = midpoint - scale * vector
antivector = scale * np.array([vector[1], -1 * vector[0]])
return [orthpoint + antivector, midpoint, orthpoint - antivector,
orthpoint + antivector, (None, None)]
# Mostly lifted from plotly docs
# edited to make edges separate traces s.t. can vary colors
edges_x = []
edges_y = []
texts = []
edge_colors = []
for edge in G.edges():
x0, y0 = pos[edge[0]]
x1, y1 = pos[edge[1]]
x = [x0, (x0+x1)/2, x1]
y = [y0, (y0+y1)/2, y1]
edges_x.append(x)
edges_y.append(y)
# try throwing text in for hovering?
text = G.edges[edge[0], edge[1]]['text']
texts.append(["", text, ""])
# color from valence
c = int(G.edges[edge[0], edge[1]]['valence'])
edge_colors.append(c)
arrows_x = []
arrows_y = []
arrow_colors = []
for edge in G.edges():
ar = arrow(*pos[edge[0]], *pos[edge[1]])
x,y = zip(*ar)
arrows_x.append(x)
arrows_y.append(y)
# color
c = int(G.edges[edge[0], edge[1]]['valence'])
arrow_colors.append(c)
# translate to colors
edge_colors = np.where(np.equal(edge_colors, -1), 'red', np.where(np.equal(edge_colors, 1), 'green', 'gray'))
arrow_colors = np.where(np.equal(arrow_colors, -1), 'red', np.where(np.equal(arrow_colors, 1), 'green', 'gray'))
edge_traces = []
for x,y,t,c in zip(edges_x, edges_y, texts, edge_colors):
edge_traces.append(go.Scatter(
x=x, y=y,
line=dict(width=0.5,
color=c
),
hovertemplate='%{text}<extra></extra>', text=t,
mode='lines'))
arrow_traces = []
for x,y,c in zip(arrows_x, arrows_y, arrow_colors):
arrow_traces.append(go.Scatter(
x=x, y=y,
line=dict(width=0.5, color=c),
mode='lines',
hoverinfo='skip'))
node_x = []
node_y = []
node_text = []
node_color = []
for node in G.nodes():
x, y = pos[node]
node_x.append(x)
node_y.append(y)
node_text.append(G.nodes[node]['text'])
node_color.append(int(G.nodes[node]['valence']))
node_color = np.where(np.equal(node_color, -1), 'red', np.where(np.equal(node_color, 1), 'green', 'gray'))
node_trace = go.Scatter(
x=node_x, y=node_y,
mode='markers+text',
#hovertemplate='%{text}<extra></extra>',
hoverinfo='skip',
text=node_text,
textposition='top center',
marker=dict(
size=10,
line_width=2,
color=node_color)
)
fig = go.Figure(data=arrow_traces + edge_traces + [node_trace],
layout=go.Layout(
title=f'{name}:',
titlefont_size=16,
showlegend=False,
hovermode='closest',
hoverdistance=500,
margin=dict(b=20,l=5,r=5,t=40),
annotations=[ dict(
showarrow=False,
xref="paper", yref="paper",
x=0.005, y=-0.002 ) ],
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False))
)
fig.show()