def plot_network2(network):
"""Function that plots the network of topics.
It mainly relies on webweb: https://github.com/dblarremore/webweb
Args:
network (dictionary): computed network.
Returns:
"""
G = nx.Graph()
for node in network["nodes"]:
G.add_node(node["label"])
G.nodes[node["label"]]['isPaper'] = False
G.nodes["paper"]['isPaper'] = True
for edge in network["edges"]:
G.add_edge(edge["source"],
edge["target"],
kind=edge["kind"],
style='dashed')
# create the web
web = Web(nx_G=G)
web.display.showNodeNames = True
web.display.colorBy = 'isPaper'
web.show()
def webweb_plot(g, coms):
# create dictionary of node:community pairs for quick look up
print('Plotting with WebWeb')
coms_dict = {}
for i in range(len(coms)):
for c in coms[i]:
# this is to control for string reformatting R did...
if c[0:3] == 'HP.':
c = c.replace('.', ':')
coms_dict[c] = i
# create metadata labels for plotting
labels = {}
for i in g.nodes:
name = g.nodes[i]['Name']
if name in coms_dict.keys():
labels[i] = {
'isGene': g.nodes[i]['Type'] == 'HPO',
'name': coms_dict[name],
'Community': coms_dict[name]
}
w = Web(adjacency=nx.to_numpy_array(g), display={'nodes': labels})
# set some default visualization settings in webweb
w.display.charge = 50
w.display.sizeBy = 'degree'
# genes will be colored green
w.display.colorBy = 'Community'
w.display.charge = 10
w.display.linkLength = 5
w.display.gravity = 0.5
w.show()
def net_vis(ld_file, loci_file):
web = Web(title='webweb')
loci_path = os.path.abspath(loci_file)
loci = pandas.read_csv(loci_path)
def get_ef(l):
q = 'locus ==' + str(l)
r = loci.query(q)
return r.iloc[0]['ef']
def get_chr(l):
q = 'locus ==' + str(l)
r = loci.query(q)
return r.iloc[0]['chromo']
path = os.path.abspath(ld_file)
df = pandas.read_csv(path)
gens = df['generation'].unique()
thres = 0.005
max_locus = df['locus2'].max()
metadata = {
'ef': {
'values': [get_ef(x) for x in range(max_locus)]
},
'chromo': {
'values': [get_chr(x) for x in range(max_locus)]
},
}
for gen in gens:
q = 'generation == ' + str(gen)
this_gen = df.query(q)
max = this_gen['D'].max()
edge_list = []
for row in this_gen.itertuples():
L1 = row[2]
L2 = row[3]
D = row[4]
Gen = row[1]
if D > thres:
edge = [L1, L2, 0.1]
edge_list.append(edge)
else:
edge = [L1, L2, 0]
edge_list.append(edge)
web.networks.webweb.add_layer(adjacency=edge_list, metadata=metadata)
#web.display.scaleLinkWidth = True
web.show()
def plot_single_community_webweb(g, coms, com):
print('Plotting with WebWeb')
# create dictionary of node:community pairs for quick look up
coms_dict = {}
for i in range(len(coms)):
for c in coms[i]:
coms_dict[c] = i
# get the indexes of the nodes in the community of interest
com_indexes = []
for i in g.nodes:
name = g.nodes[i]['Name']
if name in coms_dict.keys():
if coms_dict[name] == com:
com_indexes.append(i)
# get a subset of the grapha that is just the community of interest
subgraph = g.subgraph(com_indexes)
# create a name mapping to relabel subgraph nodes starting at one
name_mapping = {}
node_count = 0
for i in subgraph.nodes:
print(i)
name_mapping[i] = node_count
node_count += 1
# relabel subgraph nodes starting at one
subgraph = nx.relabel_nodes(subgraph, name_mapping)
# create labels for the nodes for use in webweb
labels = {}
for i in subgraph.nodes:
name = subgraph.nodes[i]['Name']
if name in coms_dict.keys():
if coms_dict[name] == com:
labels[i] = {
'isGene': subgraph.nodes[i]['Type'] == 'HPO',
'name': name,
'Community': coms_dict[name]
}
# plot it using webweb
w = Web(adjacency=nx.to_numpy_array(subgraph), display={'nodes': labels})
# set some default visualization settings in webweb
w.display.charge = 50
w.display.sizeBy = 'degree'
w.display.colorBy = 'isGene'
w.display.charge = 20
w.display.linkLength = 50
w.display.gravity = 0.1
w.show()
def display_with_webweb(graph, section_sequence):
print("Displaying graph using webweb...")
web = Web(title='book')
web.display.colorBy = 'degree'
web.display.sizeBy = 'degree'
web.display.l = 60
web.display.c = 120
web.display.scaleLinkWidth = True
for G in graph.graph_by_sections(section_sequence,
aggregate=True,
decay_weights=True,
stability=40):
web.networks.book.add_layer(nx_G=G)
web.show()
def visual_graph(all_bands):
edge_list = []
b = []
i = 0
for band_id in all_bands:
i +=1
# if i > 100:
# break
if all_bands[band_id]["is_dup"]:
continue
for to in all_bands[band_id]["in_conns"]:
if all_bands[to]["is_dup"]:
to = all_bands[to]["link_to"]
edge_list.append([band_id, to])
edge_list.append([to, band_id])
if set(all_bands[band_id]["genres"]) == {"rock"}:
group = 'R'
elif set(all_bands[band_id]["genres"]) == {"country"}:
group = 'C'
elif set(all_bands[band_id]["genres"]) == {"metal"}:
group = "M"
elif set(all_bands[band_id]["genres"]) == {"rock", "country"}:
group = "R+C"
elif set(all_bands[band_id]["genres"]) == {"rock", "metal"}:
group = "R+M"
elif set(all_bands[band_id]["genres"]) == {"country", "metal"}:
group = "C+M"
elif set(all_bands[band_id]["genres"]) == {"rock", "country", "metal"}:
group = "R+C+M"
else:
raise Exception("Band with unspecified group")
b.append([band_id, group])
web = Web(title='sbm_demo',
# assign its edgelist
adjacency=edge_list,
# give it the community metadata
nodes={i: {'Genre': g} for i, g in b},
# display={"metadata": {'Genre': {'values': ["R", "C", "M", "R+C", "R+M", "C+M", "R+C+M"]}}}
)
web.display.colorBy = 'Genre'
web.show()
def visualizePassingNetworks(visTitle, visInfoList):
# Visualization Parameters
width = 800
height = 480
padding = 50
#field dimensions in yards
fieldLength = 120
fieldWidth = 75
# instantiate webweb
web = Web(title=visTitle)
for item in visInfoList:
passing, libPlayers = PassingUtilities.createPassingListAndLib(item[0])
if len(passing) != 0:
A = PassingUtilities.createAdjacencyMatrix(passing, libPlayers)
displayInfo = createMetaData(libPlayers, width, height, padding,
fieldLength, fieldWidth)
web.networks.__dict__[item[1]] = webweb.webweb.Network(
adjacency=A, metadata=displayInfo)
web.display.charge = 500
web.display.linkLength = 200
web.display.linkStrength = 0.5
web.display.gravity = .1
web.display.radius = 10
web.display.scaleLinkOpacity = True
web.display.colorBy = 'team'
web.display.scaleLinkWidth = True
web.display.sizeBy = 'strength'
web.display.showNodeNames = True
web.display.showLegend = True
web.display.colorPalette = 'Dark2'
web.display.freezeNodeMovement = True
web.display.width = width
web.display.height = height
web.display.attachWebwebToElementWithId = 'soccer-vis'
web.show()
from webweb import Web
# Instantiate webweb object
web = Web(
[[0, 1], [1, 2], [2, 3], [3, 4], [4, 5]],
display={
'metadata': {
'emotion': {
'values': ['happy', 'sad', 'angry', 'sad', 'happy', 'sad']
}
}
})
# use the 'emotion' attribute to color nodes
web.display.colorBy = 'emotion'
# show the visualization
web.show()
def make_network(data):
nodes = defaultdict(dict)
edges = []
all_edges = []
interests = data["areas"]["topics"]
projects = data["projects"]["projects"]
project_areas = set()
for project in projects:
name = project["name"]
nodes[name] = {"name": name, "kind": "Project"}
for area in project["areas"]:
all_edges.append([name, area])
project_areas.add(area)
for interest in interests:
area = interest["area"]
# if area not in project_areas:
# continue
nodes[area] = {"name": area, "kind": interest["kind"]}
if not interest["related"]:
continue
for related in interest["related"]:
all_edges.append([area, related])
# Get only unique edges
for edge in all_edges:
if edge in edges or [edge[1], edge[0]] in edges:
continue
edges.append(edge)
for node in nodes:
kind = nodes[node]['kind']
size = 1
# if kind == 'Theory':
# size = 1.5
# elif kind == 'Application':
# size = 1.25
nodes[node]['size'] = size
nodes[node]['color'] = KIND_TO_COLOR_MAP[kind]
web = Web(adjacency=edges, nodes=dict(nodes))
web.display.sizeBy = 'size'
web.display.colorBy = 'color'
web.display.hideMenu = True
web.display.showLegend = False
web.display.gravity = 1e-5
web.display.charge = 500
web.display.width = 400
web.display.height = 400
web.display.scaleLinkOpacity = True
web.display.scaleLinkWidth = True
web.display.scales = {
'nodeSize': {
'min': 0.65,
'max': 1.1,
}
}
WEBWEB_JSON_PATH.write_text(web.json)
web.show()