def category(request, name):
from data_categories import CATEGORIES
name = CATEGORY_NAME_PREFIX + name
category = CATEGORIES.get(name)
if not category:
raise Http404
#print category.get_absolute_url()
parents = category.parents.order_by('display')
children = category.children.order_by('display')
try:
changes = []
annotations = []
for chao in category.chao.all():
for change in chao.changes.filter(Change.relevant_filter).order_by('-timestamp'):
changes.append(change)
for annotation in chao.annotations.filter(Annotation.relevant_filter).order_by('-created'):
annotations.append(annotation)
#print changes
#print annotations
except OntologyComponent.DoesNotExist:
changes = annotations = []
timeline_changes = get_weekly(changes, lambda c: c.timestamp.date() if c.timestamp else None, to_ordinal=True,
min_date=MIN_CHANGES_DATE, max_date=MAX_CHANGES_DATE)
timeline_annotations = get_weekly(annotations, lambda a: a.created.date() if a.created else None, to_ordinal=True,
min_date=MIN_CHANGES_DATE, max_date=MAX_CHANGES_DATE)
authors = counts(change.author_id for change in changes + annotations)
authors = [{'label': name[len(settings.INSTANCE):], 'data': count} for name, count in sorted(authors.iteritems(),
key=lambda (n, c): c, reverse=True)]
#x, y = GRAPH_POSITIONS[settings.DEFAULT_LAYOUT][category.name]
x, y = category.get_pos(settings.DEFAULT_LAYOUT)
network_url = reverse('icd.views.network') + '#x=%f&y=%f&z=2' % (x, y)
return render_to_response('category.html', {
'category': category,
'parents': parents,
'children': children,
'changes': changes,
'annotations': annotations,
'network_url': network_url,
'timeline_changes': timeline_changes,
'timeline_annotations': timeline_annotations,
'authors': authors,
}, context_instance=RequestContext(request))
import util
import matplotlib.pyplot as plt
import mysql.connector
if __name__ == "__main__":
connection = mysql.connector.connect(host="127.0.0.1",
port=3307,
user='******',
password='******',
db='weibo')
cur = connection.cursor()
hot_keyword = util.get_top_hot_words("data/result.json", True, True, True,
10)
search_result = util.search_by_single_keyword(cur, "人传人")
freq1 = util.counts(search_result, "2020-01-20 00:00:00",
"2020-01-25 00:00:00", 'H')
search_result = util.search_by_single_keyword(cur, "钟南山")
freq2 = util.counts(search_result, "2020-01-20 00:00:00",
"2020-01-25 00:00:00", "H")
plt.scatter(freq1["counts"], freq2["counts"])
plt.savefig("images/scatter_.png")
def test_count():
connection = mysql.connector.connect(host="127.0.0.1",
port=3307,
user='******',
password='******',
db='weibo')
cur = connection.cursor()
result = util.counts(cur, "人传人", "", "IGNORE", "2020-01-21 00:00:00",
"2020-01-25 00:00:00", 'H')
assert result["counts"][0] >= 3104
assert result["counts"][1] >= 1273
assert result["counts"][2] >= 588
assert result["counts"][3] >= 356
assert result["counts"][4] >= 303
assert result["counts"][5] >= 483
assert result["counts"][6] >= 906
assert result["counts"][7] >= 2037
assert result["counts"][8] >= 2519
assert result["counts"][9] >= 2587
assert result["counts"][10] >= 2072
result = util.counts(cur, "一级响应", "", "IGNORE", "2020-01-23 22:00:00",
"2020-01-25 00:00:00", 'H')
assert result["counts"][0] >= 67
assert result["counts"][1] >= 172
assert result["counts"][2] >= 128
assert result["counts"][3] >= 82
assert result["counts"][4] >= 20
assert result["counts"][5] >= 9
assert result["counts"][6] >= 11
assert result["counts"][7] >= 8
assert result["counts"][8] >= 10
assert result["counts"][9] >= 32
assert result["counts"][10] >= 45
assert result["counts"][11] >= 40
assert result["counts"][12] >= 45
assert result["counts"][13] >= 33
assert result["counts"][14] >= 148
assert result["counts"][15] >= 191
assert result["counts"][16] >= 180
assert result["counts"][17] >= 192
result = util.counts(cur, "浙江", "一级响应", "AND", "2020-01-23 22:00:00",
"2020-01-25 00:00:00", 'H')
assert result["counts"][0] >= 52
assert result["counts"][1] >= 78
assert result["counts"][2] >= 62
assert result["counts"][3] >= 49
assert result["counts"][4] >= 11
assert result["counts"][5] >= 7
assert result["counts"][6] >= 5
assert result["counts"][7] >= 6
assert result["counts"][8] >= 7
assert result["counts"][9] >= 26
assert result["counts"][10] >= 34
assert result["counts"][11] >= 36
assert result["counts"][12] >= 41
assert result["counts"][13] >= 27
assert result["counts"][14] >= 121
assert result["counts"][15] >= 161
assert result["counts"][16] >= 134
assert result["counts"][17] >= 162
assert result["counts"][0] <= 67
assert result["counts"][1] <= 172
assert result["counts"][2] <= 128
assert result["counts"][3] <= 82
assert result["counts"][4] <= 20
assert result["counts"][5] <= 9
assert result["counts"][6] <= 11
assert result["counts"][7] <= 8
assert result["counts"][8] <= 10
assert result["counts"][9] <= 32
assert result["counts"][10] <= 45
assert result["counts"][11] <= 40
assert result["counts"][12] <= 45
assert result["counts"][13] <= 33
assert result["counts"][14] <= 148
assert result["counts"][15] <= 191
assert result["counts"][16] <= 180
assert result["counts"][17] <= 192
result = util.counts(cur, "浙江", "广东", "OR", "2020-01-23 22:00:00",
"2020-01-25 00:00:00", 'H')
assert result["counts"][0] >= 103
assert result["counts"][1] >= 197
assert result["counts"][2] >= 146
assert result["counts"][3] >= 96
assert result["counts"][4] >= 31
assert result["counts"][5] >= 19
assert result["counts"][6] >= 17
assert result["counts"][7] >= 16
assert result["counts"][8] >= 21
result = util.counts(cur, "浙江", "广东", "ERRORTEST", "2020-01-23 22:00:00",
"2020-01-25 00:00:00", 'H')
assert len(result["counts"]) == 0
def category(request, name):
INSTANCE = get_instance(request)
#from data_categories import CATEGORIES
test = ""
if name.startswith("http:/") and not name.startswith("http://"):
test = "i do parse wrong"
name = name.replace("http:/", "http://", 1)
print name
category = data_categories.CATEGORIES[INSTANCE].get(name)
if not category:
raise Http404
#print category.get_absolute_url()
parents = category.parents.order_by('display')
children = category.children.order_by('display')
try:
changes = []
annotations = []
for chao in category.chao.all():
for change in chao.changes.filter(relevant_filter(INSTANCE)).order_by('-timestamp'):
changes.append(change)
for annotation in chao.annotations.filter(Annotation.relevant_filter).order_by('-created'):
annotations.append(annotation)
#print changes
#print annotations
except OntologyComponent.DoesNotExist:
changes = annotations = []
tag_activity = [{'label': 'Primary Community Changes', 'data': category.metrics.primary_tag_changes},
{'label': 'Secondary Community Changes', 'data': category.metrics.secondary_tag_changes},
{'label': 'Involved Community Changes', 'data': category.metrics.involved_tag_changes},
{'label': 'WHO Team Community Changes', 'data': category.metrics.who_tag_changes},
{'label': 'Outside Community Changes', 'data': category.metrics.outside_tag_changes}]
timeline_changes = get_weekly(changes, lambda c: c.timestamp.date() if c.timestamp else None, to_ordinal=True,
min_date=data.MIN_CHANGES_DATE[INSTANCE], max_date=data.MAX_CHANGES_DATE[INSTANCE])
timeline_annotations = get_weekly(annotations, lambda a: a.created.date() if a.created else None, to_ordinal=True,
min_date=data.MIN_CHANGES_DATE[INSTANCE], max_date=data.MAX_CHANGES_DATE[INSTANCE])
authors = counts(change.author_id for change in changes + annotations)
authors = [{'label': name[len(INSTANCE):], 'data': count} for name, count in sorted(authors.iteritems(),
key=lambda (n, c): c, reverse=True)]
titles = category.category_titles.all()
definitions = category.category_definitions.all()
involved_tags = category.involved_tags.all()
#x, y = GRAPH_POSITIONS[settings.DEFAULT_LAYOUT][category.name]
x, y = category.get_pos(settings.DEFAULT_LAYOUT)
network_url = reverse('icd.views.network') + '#x=%f&y=%f&z=2' % (x, y)
#reCoIndations = [x.reCoInd for x in category.similarity_reCoIndations.all().order_by("-tag_similarity")[:10]]
#coeditor_reCoIndations = [x.reCoInd for x in category.amazon_reCoIndations.all().order_by("-tag_similarity")]
return render_to_response('category.html', {
'instance': INSTANCE,
#'instances': settings.INSTANCES,
'name': name,
'test': test,
'category': category,
'parents': parents,
'children': children,
'changes': changes,
'annotations': annotations,
'network_url': network_url,
'timeline_changes': timeline_changes,
'timeline_annotations': timeline_annotations,
'authors': authors,
'titles': titles,
'tag_activity': tag_activity,
#'reCoIndations': reCoIndations,
'definitions': definitions,
'involved_tags': involved_tags,
#'coeditor_reCoIndations': coeditor_reCoIndations,
}, context_instance=RequestContext(request))
pvals_pri, pvals_fol = (primary_data.flat[0]['pvals'],
followup_data.flat[0]['pvals'])
# Extract raw data for permutation testing
rvs_a_pri, rvs_b_pri = (primary_data.flat[0]['rvs_a'],
primary_data.flat[0]['rvs_b'])
rvs_a_fol, rvs_b_fol = (followup_data.flat[0]['rvs_a'],
followup_data.flat[0]['rvs_b'])
"""Define analysis parameters."""
n_iterations, n_effect_sizes, nl, _ = np.shape(pvals_pri)
emph_primary = 0.1
alpha = 0.05
method = qvalue
sl = 30 # TODO: save to .npy file.
"""Compute reproducibility rates."""
rr = np.zeros([n_iterations, n_effect_sizes])
for ind in np.ndindex(n_iterations, n_effect_sizes):
print('Analysis iteration %3d' % (1 + ind[0]))
replicable = repl(pvals_pri[ind].flatten(), pvals_fol[ind].flatten(),
emph_primary, method, alpha)
replicable = np.reshape(replicable, [nl, nl])
rr[ind] = counts(replicable, nl, sl)[0]
"""Save data to disk."""
output_fpath = fpath
output_fname = output_fpath + ('/result-%s.npy' % method.__name__)
np.save(output_fname, {'rr': rr})
print('Results saved to disk.')
