def projects_morelab_collaborations(request):
G = nx.Graph()
projects = Project.objects.all()
pr_role = Role.objects.get(slug='principal-researcher')
for project in projects:
person_ids = AssignedPerson.objects.filter(project_id=project.id).exclude(role_id=pr_role.id).values('person_id')
if person_ids:
_list = [person_id['person_id'] for person_id in person_ids]
for pos, person_id in enumerate(_list):
for i in range(pos+1, len(_list)):
person1 = Person.objects.get(id=person_id)
person2 = Person.objects.get(id=_list[i])
if person1.is_active and person2.is_active:
G.add_edge(person1.id, person2.id)
try:
G[person1.id][person2.id]['weight'] += 1
except:
G[person1.id][person2.id]['weight'] = 1
G.node[person1.id]['name'] = person1.full_name
G.node[person2.id]['name'] = person2.full_name
G = nx_graph.analyze(G)
data = json_graph.node_link_data(G)
# dictionary to be returned in render_to_response()
return_dict = {
'web_title': u'Group collaborations',
'data': json.dumps(data),
}
return render_to_response("charts/projects/collaboration_morelab.html", return_dict, context_instance=RequestContext(request))
def project_collaborations(request, exclude_leaders=False, within_group=False):
G = nx.Graph()
projects = Project.objects.all()
names = set()
for project in projects:
if exclude_leaders:
person_ids = AssignedPerson.objects.filter(
project=project
).exclude(
role__exclude_from_charts=True
).values_list('person_id', flat=True)
else:
person_ids = AssignedPerson.objects.filter(
project=project
).values_list('person_id', flat=True)
if person_ids:
for pos, person_id in enumerate(person_ids):
for i in range(pos+1, len(person_ids)):
person1 = Person.objects.get(id=person_id)
person2 = Person.objects.get(id=person_ids[i])
names.add(person1.full_name)
names.add(person2.full_name)
add_node = True
if within_group and (not person1.is_active or not person2.is_active):
add_node = False
if add_node:
G.add_edge(person1.id, person2.id)
try:
G[person1.id][person2.id]['weight'] += 1
except:
G[person1.id][person2.id]['weight'] = 1
G.node[person1.id]['name'] = person1.full_name
G.node[person2.id]['name'] = person2.full_name
G = nx_graph.analyze(G)
data = json_graph.node_link_data(G)
return_dict = {
'data': json.dumps(data),
'names': list(names),
'web_title': u'Group collaborations',
'within_group': within_group,
}
return render(request, "charts/projects/collaboration.html", return_dict)
def publication_coauthorships(request, max_position=None, within_group=False):
G = nx.Graph()
if max_position and int(max_position) > 1:
pub_authors = PublicationAuthor.objects.exclude(position__gt=max_position)
else:
pub_authors = PublicationAuthor.objects.all()
pub_authors = pub_authors.values("publication_id", "author_id", "author_id__full_name")
# 'publication_id': [ pub_author1, pub_author2, pub_author3 ]
authors_per_publication = defaultdict(list)
if within_group:
people = Person.objects.all().values("is_active", "id")
active_by_id = {}
for person in people:
active_by_id[person['id']] = person['is_active']
for pub_author in pub_authors:
check_coauthorship = True
if within_group and not active_by_id[pub_author['author_id']]:
check_coauthorship = False
if check_coauthorship:
entry = (pub_author['author_id'], pub_author['author_id__full_name'])
authors_per_publication[pub_author['publication_id']].append(entry)
for relations in authors_per_publication.values():
for (author_id1, name1), (author_id2, name2) in combinations(relations, 2):
G.add_edge(author_id1, author_id2)
try:
G[author_id1][author_id2]['weight'] += 1
except:
G[author_id1][author_id2]['weight'] = 1
G.node[author_id1]['name'] = name1
G.node[author_id2]['name'] = name2
G = nx_graph.analyze(G)
data = json_graph.node_link_data(G)
return_dict = {
'data': json.dumps(data),
'web_title': u'Publications co-authorship',
'within_group': within_group,
}
return render(request, "charts/publications/co_authorship.html", return_dict)
def publications_egonetwork(request, author_slug):
author = get_object_or_404(Person, slug=author_slug)
G = nx.Graph()
pub_authors = PublicationAuthor.objects.all().values(
"publication_id", "author_id", "author_id__full_name")
authors_per_publication = defaultdict(
list) # 'publication_id': [ pub_author1, pub_author2, pub_author3 ]
for pub_author in pub_authors:
entry = (pub_author['author_id'], pub_author['author_id__full_name'])
authors_per_publication[pub_author['publication_id']].append(entry)
for relations in authors_per_publication.values():
for (author_id1, name1), (author_id2,
name2) in combinations(relations, 2):
G.add_edge(author_id1, author_id2)
try:
G[author_id1][author_id2]['weight'] += 1
except:
G[author_id1][author_id2]['weight'] = 1
G.node[author_id1]['name'] = name1
G.node[author_id2]['name'] = name2
try:
G = nx_graph.analyze(G)
ego_g = nx.ego_graph(G, author.id)
data = json_graph.node_link_data(ego_g)
except:
data = {}
# dictionary to be returned in render(request, )
return_dict = {
# 'publication_tags_per_year': publication_tags_per_year,
'web_title': u'%s - Egonetwork' % author.full_name,
'data': json.dumps(data),
'author': author,
}
return render(request, "charts/publications/egonetwork.html", return_dict)
def publications_morelab_coauthorship(request, max_position=None):
G = nx.Graph()
if max_position and int(max_position) > 1:
pub_authors = PublicationAuthor.objects.exclude(position__gt=max_position).values("publication_id", "author_id", "author_id__full_name")
else:
pub_authors = PublicationAuthor.objects.all().values("publication_id", "author_id", "author_id__full_name")
people = Person.objects.all().values("is_active", "id")
active_by_id = {}
for person in people:
active_by_id[person['id']] = person['is_active']
authors_per_publication = defaultdict(list) # 'publication_id': [ pub_author1, pub_author2, pub_author3 ]
for pub_author in pub_authors:
if active_by_id[pub_author['author_id']]:
entry = (pub_author['author_id'], pub_author['author_id__full_name'])
authors_per_publication[pub_author['publication_id']].append(entry)
for relations in authors_per_publication.values():
for (author_id1, name1), (author_id2, name2) in combinations(relations, 2):
G.add_edge(author_id1, author_id2)
try:
G[author_id1][author_id2]['weight'] += 1
except:
G[author_id1][author_id2]['weight'] = 1
G.node[author_id1]['name'] = name1
G.node[author_id2]['name'] = name2
G = nx_graph.analyze(G)
data = json_graph.node_link_data(G)
# dictionary to be returned in render_to_response()
return_dict = {
'web_title': u'Group publications co-authorship',
'data': json.dumps(data),
}
return render_to_response("charts/publications/co_authorship.html", return_dict, context_instance=RequestContext(request))
def publications_egonetwork(request, author_slug):
author = get_object_or_404(Person, slug=author_slug)
G = nx.Graph()
pub_authors = PublicationAuthor.objects.all().values("publication_id", "author_id", "author_id__full_name")
authors_per_publication = defaultdict(list) # 'publication_id': [ pub_author1, pub_author2, pub_author3 ]
for pub_author in pub_authors:
entry = (pub_author['author_id'], pub_author['author_id__full_name'])
authors_per_publication[pub_author['publication_id']].append(entry)
for relations in authors_per_publication.values():
for (author_id1, name1), (author_id2, name2) in combinations(relations, 2):
G.add_edge(author_id1, author_id2)
try:
G[author_id1][author_id2]['weight'] += 1
except:
G[author_id1][author_id2]['weight'] = 1
G.node[author_id1]['name'] = name1
G.node[author_id2]['name'] = name2
try:
G = nx_graph.analyze(G)
ego_g = nx.ego_graph(G, author.id)
data = json_graph.node_link_data(ego_g)
except:
data = {}
# dictionary to be returned in render(request, )
return_dict = {
# 'publication_tags_per_year': publication_tags_per_year,
'web_title': u'%s - Egonetwork' % author.full_name,
'data': json.dumps(data),
'author': author,
}
return render(request, "charts/publications/egonetwork.html", return_dict)
def publication_coauthorships(request, max_position=None, within_group=False):
G = nx.Graph()
if max_position and int(max_position) > 1:
pub_authors = PublicationAuthor.objects.exclude(
position__gt=max_position)
else:
pub_authors = PublicationAuthor.objects.all()
pub_authors = pub_authors.values("publication_id", "author_id",
"author_id__full_name")
# 'publication_id': [ pub_author1, pub_author2, pub_author3 ]
authors_per_publication = defaultdict(list)
names = set()
if within_group:
people = Person.objects.all().values("is_active", "id")
active_by_id = {}
for person in people:
active_by_id[person['id']] = person['is_active']
for pub_author in pub_authors:
check_coauthorship = True
if within_group and not active_by_id[pub_author['author_id']]:
check_coauthorship = False
if check_coauthorship:
entry = (pub_author['author_id'],
pub_author['author_id__full_name'])
authors_per_publication[pub_author['publication_id']].append(entry)
for relations in authors_per_publication.values():
for (author_id1, name1), (author_id2,
name2) in combinations(relations, 2):
G.add_edge(author_id1, author_id2)
try:
G[author_id1][author_id2]['weight'] += 1
except:
G[author_id1][author_id2]['weight'] = 1
G.node[author_id1]['name'] = name1
G.node[author_id2]['name'] = name2
names.add(name1)
names.add(name2)
try:
G = nx_graph.analyze(G)
except:
# Avoid networkx's "power iteration failed to converge" error
pass
data = json_graph.node_link_data(G)
return_dict = {
'data': json.dumps(data),
'names': list(names),
'web_title': u'Publications co-authorship',
'within_group': within_group,
}
return render(request, "charts/publications/co_authorship.html",
return_dict)
