def test_get_publication_data(self):
'''Test getting publication data'''
from models import get_publication_data
data = get_publication_data(testset)
# The most important thing here is to test that it is a list
# of MetricsModel instances
self.assertEqual(isinstance(data, list), True)
self.assertTrue(False not in
[x.__class__.__name__ == 'MetricsModel' for x in data])
def test_get_publication_data(self):
'''Test getting publication data'''
from models import get_publication_data
data = get_publication_data(testset)
# The most important thing here is to test that it is a list
# of MetricsModel instances
self.assertEqual(isinstance(data, list), True)
self.assertTrue(
False not in [x.__class__.__name__ == 'MetricsModel' for
x in data])
def get_publication_histograms(identifiers):
ph = {}
current_year = datetime.now().year
# Get necessary data
data = get_publication_data(identifiers)
# Get the publication histogram
years = [int(p.bibcode[:4]) for p in data]
nullhist = [(y, 0) for y in range(min(years), current_year + 1)]
yearhist = cy.frequencies(years)
ph['all publications'] = merge_dictionaries(dict(nullhist), yearhist)
years_ref = [int(p.bibcode[:4]) for p in data if p.refereed]
yearhist = cy.frequencies(years_ref)
ph['refereed publications'] = merge_dictionaries(dict(nullhist), yearhist)
# Get the normalized publication histogram
tmp = [(int(p.bibcode[:4]), 1.0 / float(p.author_num)) for p in data]
ph['all publications normalized'] = get_norm_histo(nullhist + tmp)
tmp = [(int(p.bibcode[:4]), 1.0 / float(p.author_num)) for p in data
if p.refereed]
ph['refereed publications normalized'] = get_norm_histo(nullhist + tmp)
return ph
def get_publication_histograms(identifiers):
ph = {}
current_year = datetime.now().year
# Get necessary data
data = get_publication_data(identifiers)
# Get the publication histogram
years = [int(p.bibcode[:4]) for p in data]
nullhist = [(y, 0) for y in range(min(years), current_year + 1)]
yearhist = cy.frequencies(years)
ph['all publications'] = merge_dictionaries(dict(nullhist), yearhist)
years_ref = [int(p.bibcode[:4]) for p in data if p.refereed]
yearhist = cy.frequencies(years_ref)
ph['refereed publications'] = merge_dictionaries(dict(nullhist), yearhist)
# Get the normalized publication histogram
tmp = [(int(p.bibcode[:4]), 1.0 / float(p.author_num)) for p in data]
ph['all publications normalized'] = get_norm_histo(nullhist + tmp)
tmp = [(int(p.bibcode[:4]), 1.0 / float(p.author_num))
for p in data if p.refereed]
ph['refereed publications normalized'] = get_norm_histo(nullhist + tmp)
return ph
