from collections import Counter, defaultdict
from operator import itemgetter
import matplotlib.pyplot as plt
from scholarmetrics import hindex
from scopus import AbstractRetrieval, AuthorRetrieval, ScopusSearch
def get_subject_docs(identifier, refresh):
"""Returns (subject area, number of documents)-tuples."""
au = AuthorRetrieval(identifier, refresh=refresh)
docs = dict(au.classificationgroup)
names = [(p.area, docs[p.code]) for p in au.subject_areas]
names.sort(reverse=True, key=itemgetter(1))
return names
[docs]def report(query, label, refresh=True):
"""Print out an org-mode report for search results.
Parameters
----------
query : str
The search query based on which results the report should be
generated.
label : str
The label used in the document title ("Report for ...").
refresh : bool (optional, default=True)
Whether to refresh a cached file containing results of a previous
query or not.
"""
# Header
print('*** Report for {}\n'.format(label))
print('#+attr_latex: :placement [H] :center nil')
# Perform query
s = ScopusSearch(query, refresh=refresh)
journal_res = [p for p in s.results if p.aggregationType == "Journal"]
# Parse results
doc_types = Counter([p.aggregationType for p in s.results])
paper_cites = {(p.title, p.doi): int(p.citedby_count) for p in journal_res}
Ncites = sum(paper_cites.values())
papers = len(journal_res)
author_count = [len(p.authid.split(";")) for p in journal_res]
au_counts = defaultdict(lambda: 0)
j_counts = defaultdict(lambda: 0)
for p in journal_res:
for auth in zip(p.authname.split(";"), p.authid.split(";")):
key = (auth[0], auth[1])
au_counts[key] += 1
jkey = (p.publicationName, p.source_id, p.issn)
j_counts[jkey] += 1
# Document information
print('#+caption: Types of documents found for {}.'.format(label))
print('| Document type | count |\n|-')
for key, value in doc_types.items():
print('| {} | {} |'.format(key, value))
print('\n\n{} articles ({} citations) '
'found by {} authors'.format(papers, Ncites, len(au_counts)))
# Author counts {(name, scopus-id): count}
auth_url = "[[https://www.scopus.com/authid/detail.uri?authorId={}][{}]]"
view = [(auth_url.format(k[1], k[0]), v, k[1])
for k, v in au_counts.items()]
view.sort(reverse=True, key=itemgetter(1))
print('\n#+attr_latex: :placement [H] :center nil')
print('#+caption: Author publication counts for {0}.'.format(label))
print('| name | count | categories |\n|-')
for name, count, identifier in view[:20]:
cats = ', '.join(['{} ({})'.format(cat[0], cat[1])
for cat in get_subject_docs(identifier, refresh)[0:3]])
print('| {} | {} | {} |'.format(name, count, cats))
# Journal information
jour_url = '[[https://www.scopus.com/source/sourceInfo.url?sourceId={}][{}]]'
jview = [(jour_url.format(k[1], k[0][0:50]), k[1], k[2], v)
for k, v in j_counts.items()]
jview.sort(reverse=True, key=itemgetter(3))
print('\n\n#+attr_latex: :placement [H] :center nil')
print('#+caption: Journal publication counts for {}.'.format(label))
print('| Journal | count |\n|-')
for journal, sid, issn, count in jview[0:12]:
print('| {} | {} |'.format(journal, count))
# Top cited papers
pview = [('[[{}][{}]]'.format(k[1], k[0][0:60]), int(v))
for k, v in paper_cites.items()]
pview.sort(reverse=True, key=itemgetter(1))
h_index = hindex([p[1] for p in pview])
print('\n\n#+attr_latex: :placement [H] :center nil')
print('#+caption: Top cited publication'
' counts for {}. h-index = {}.'.format(label, h_index))
print('| title | cite count |\n|-')
for title, count in pview[0:10]:
print('| {} | {} |'.format(title, count))
# Plot authors per publication
plt.figure()
plt.hist(author_count, 20)
plt.xlabel('# authors')
plt.ylabel('frequency')
plt.savefig('{}-nauthors-per-publication.png'.format(label))
# Bibliography
print('\n\n#+caption: Number of authors '
'on each publication for {}.'.format(label))
print('[[./{}-nauthors-per-publication.png]]'.format(label))
print('''**** Bibliography :noexport:
:PROPERTIES:
:VISIBILITY: folded
:END:''')
for i, p in enumerate(journal_res):
abstract = AbstractRetrieval(p.eid)
print('{}. {}\n'.format(i + 1, abstract))
