Source code for inspirehep.modules.authors.rest.stats
# -*- coding: utf-8 -*-
#
# This file is part of INSPIRE.
# Copyright (C) 2014-2017 CERN.
#
# INSPIRE is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# INSPIRE is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with INSPIRE. If not, see <http://www.gnu.org/licenses/>.
#
# In applying this license, CERN does not waive the privileges and immunities
# granted to it by virtue of its status as an Intergovernmental Organization
# or submit itself to any jurisdiction.
from __future__ import absolute_import, division, print_function
import json
from collections import Counter
from elasticsearch_dsl import Q
from inspire_utils.helpers import force_list
from inspire_utils.record import get_value
from inspirehep.modules.search import LiteratureSearch
from inspirehep.utils.stats import calculate_h_index, calculate_i10_index
[docs]class AuthorAPIStats(object):
"""API endpoint for author collection returning statistics."""
[docs] def serialize(self, pid, record, links_factory=None):
"""Return a different metrics for a given author recid.
:param pid:
Persistent identifier instance.
:param record:
Record instance.
:param links_factory:
Factory function for the link generation, which are added to
the response.
"""
author_pid = pid.pid_value
fields = set()
keywords = []
statistics = {}
statistics['citations'] = 0
statistics['publications'] = 0
statistics['types'] = {}
statistics_citations = {}
query = Q('match', authors__recid=author_pid)
search = LiteratureSearch().query('nested', path='authors', query=query)\
.params(_source=[
'citation_count',
'control_number',
'facet_inspire_doc_type',
'facet_inspire_categories',
'keywords',
])
for result in search.scan():
result_source = result.to_dict()
# Increment the count of the total number of publications.
statistics['publications'] += 1
# Increment the count of citations.
citation_count = result_source.get('citation_count', 0)
statistics['citations'] += citation_count
statistics_citations[result_source['control_number']] = \
citation_count
# Count how many times certain type of publication was published.
try:
publication_type = result_source.get(
'facet_inspire_doc_type', [])[0]
except IndexError:
pass
if publication_type:
if publication_type in statistics['types']:
statistics['types'][publication_type] += 1
else:
statistics['types'][publication_type] = 1
# Get fields.
for field in result_source.get('facet_inspire_categories', []):
fields.add(field)
# Get keywords.
keywords.extend([
k for k in force_list(
get_value(result_source, 'keywords.value'))
if k != '* Automatic Keywords *'])
# Calculate h-index together with i10-index.
statistics['hindex'] = calculate_h_index(statistics_citations)
statistics['i10index'] = calculate_i10_index(statistics_citations)
if fields:
statistics['fields'] = list(fields)
# Return the top 25 keywords.
if keywords:
counter = Counter(keywords)
statistics['keywords'] = [{
'count': i[1],
'keyword': i[0]
} for i in counter.most_common(25)]
return json.dumps(statistics)