def getPeriodInfo(self, bid, start, period, sample, c=None, total=None):
close_cursor = False
if c is None:
c = self.db.cursor()
close_cursor = True
query = self._get_period_info_query()
t = [bid, start, start + period]
if sample.lower() != 'all':
t.append(sample)
query += " AND lb = ?"
# print "query: %s, var: %s" % (query, str(t))
logging.debug(query + str(t))
c.execute(query, t)
row = c.fetchone()
ret = {'name': sample, 'count': row[0],
'avgt': row[1], 'maxt': row[2], 'mint': row[3],
'stddevt': row[4], 'medt': row[5], 'p10t': row[6],
'p90t': row[7], 'p95t': row[8], 'p98t': row[9],
'total': row[10], 'success': row[11],
'tput': row[0] / float(period),
'filename': str2id(sample),
'title': str2id(sample | truncate(20))}
ret['error'] = int(ret['count'] - ret['success'])
ret['success_rate'] = 100.
if ret['count'] > 0:
ret['success_rate'] = (100. * ret['success']) / ret['count']
if total is None or not total:
ret['percent'] = 100.
else:
ret['percent'] = ret['total'] * 100. / total
if close_cursor:
c.close()
return ret
def incorporate_row(row, graph):
general_election_id = ns_election['72'] # change after the next elections
bsq = int(row[6])
division_id = next(graph.subjects(ns_property.dgeqDivisionId, Literal(bsq)))
lastname = row[9]
firstname = row[10]
gender = 'female' if row[7] == 'F' else 'male'
candidate_id = ns_candidate[str2id(lastname + '_' + firstname)]
graph.add((candidate_id, FOAF.gender, Literal(gender)))
query = """select distinct ?run ?party where {
?elecnode rdf:type type:ProvincialElection .
?elecnode prop:generalElection <%s> .
?elecnode prop:division <%s> .
?run prop:election ?elecnode .
?run prop:runningCandidate <%s> .
?run prop:runningFor ?party .
}
""" % (general_election_id, division_id, candidate_id)
qres = graph.query(query, initNs={'rdf': RDF, 'prop': ns_property, 'type': ns_type})
assert len(qres) == 1
run_id, party_id = list(qres)[0]
graph.add((run_id, ns_property.dgeqRunId, Literal(int(row[1]))))
graph.add((run_id, ns_property.dateRegistered, Literal(row[11])))
graph.add((party_id, RDF.type, FOAF.Organization))
graph.add((party_id, FOAF.name, Literal(row[3])))
agent_name = row[5]
try:
lastname, firstname = agent_name.split(', ')
agent_id = ns_agent[str2id(lastname + '_' + firstname)]
save_person(graph, agent_id, firstname, lastname)
graph.add((run_id, ns_property.registrationAgent, agent_id))
except ValueError:
pass # seriously, those damn freaking messed up names... we don't care about them.
def getPeriodInfo(self, bid, start, period, sample, c=None, total=None):
close_cursor = False
if c is None:
c = self.db.cursor()
close_cursor = True
query = self._get_period_info_query()
t = [bid, start, start + period]
if sample.lower() != 'all':
t.append(sample)
query += " AND lb = ?"
# print "query: %s, var: %s" % (query, str(t))
logging.debug(query + str(t))
c.execute(query, t)
row = c.fetchone()
ret = {'name': sample, 'count': row[0],
'avgt': row[1], 'maxt': row[2], 'mint': row[3],
'stddevt': row[4], 'medt': row[5], 'p10t': row[6],
'p90t': row[7], 'p95t': row[8], 'p98t': row[9],
'total': row[10], 'success': row[11],
'tput': row[0] / float(period),
'filename': str2id(sample),
'title': str2id(sample | truncate(20))}
ret['error'] = int(ret['count'] - ret['success'])
ret['success_rate'] = 100.
if ret['count'] > 0:
ret['success_rate'] = (100. * ret['success']) / ret['count']
if total is None or not total:
ret['percent'] = 100.
else:
ret['percent'] = ret['total'] * 100. / total
if close_cursor:
c.close()
return ret
def get_graph_from_soup(soup, dgeqid):
graph = Graph()
# extract election year
header = soup('h2', id='e')[0].get_text()
election_year = str2int(re.findall(r"\d{4}", header)[0])
print(election_year)
table = soup('table', class_='tableau')[0]
rows = table('tr')
current_division = None
general_election_id = ns_election[dgeqid]
graph.add((general_election_id, RDF.type, ns_type.ProvincialGeneralElection))
graph.add((general_election_id, ns_property.year, Literal(election_year)))
for row in rows:
if not row.td: # header row, skip
continue
if 'circonscription-precedante' in row.td.attrs.get('class', ()): # division name row
name = row.td.get_text().strip()
current_division = ns_division[str2id(name)]
graph.add((current_division, RDF.type, ns_type.ProvincialDivision))
graph.add((current_division, DC.description, Literal(name)))
first = True
election_id = BNode()
graph.add((election_id, RDF.type, ns_type.ProvincialElection))
graph.add((election_id, ns_property.generalElection, general_election_id))
graph.add((election_id, ns_property.division, current_division))
elif row.td.attrs.get('colspan') == '4': # summary row
summary = row.td.get_text().strip()
matches = re.findall(r"(?<=:)[\s\d]+", summary)
graph.add((election_id, ns_property.validVoteCount, Literal(str2int(matches[0]))))
graph.add((election_id, ns_property.invalidVoteCount, Literal(str2int(matches[1]))))
graph.add((election_id, ns_property.totalVoteCount, Literal(str2int(matches[2]))))
graph.add((election_id, ns_property.admissibleVoterCount, Literal(str2int(matches[3]))))
else: # normal row
cells = row.find_all('td')
name = cells[0].get_text().strip()
m = re.match(r"(.+?), (.+) \((.+)\)", name)
lastname = m.group(1)
firstname = m.group(2)
party_id = str2party(m.group(3))
candidate_id = ns_candidate[str2id(lastname + '_' + firstname)]
votes = str2int(cells[1].get_text())
graph.add((candidate_id, RDF.type, ns_type.ProvincialCandidate))
save_person(graph, candidate_id, firstname, lastname)
run_id = BNode()
graph.add((run_id, RDF.type, ns_type.ProvincialCandidateRun))
graph.add((run_id, ns_property.runningCandidate, candidate_id))
graph.add((run_id, ns_property.election, election_id))
graph.add((run_id, ns_property.runningFor, party_id))
graph.add((run_id, ns_property.voteCount, Literal(votes)))
if first:
graph.add((run_id, ns_property.won, Literal(True)))
first = False
return graph
def data_generator(self, X_train, Y_train, batch_size):
# 数据生成器
X, Y = [], []
while True:
for c, t in zip(X_train, Y_train):
X.append(str2id(c, self.char2id))
Y.append(str2id(t, self.char2id,
start_end=True)) # 只需给标题加开始和结尾
if len(X) == batch_size:
X = np.array(self.padding(X))
Y = np.array(self.padding(Y))
yield [X, Y], None
X, Y = [], []
def main():
graph = Graph()
URL = 'http://www.electionsquebec.qc.ca/documents/donnees-ouvertes/Liste_circonscriptions.txt'
with urlopen(URL) as fp:
contents = fp.read().decode('utf-8')
lines = contents.splitlines()
for line in lines:
div_id, div_name = line.split(';')
current_division = ns_division[str2id(div_name)]
graph.add((current_division, RDF.type, ns_type.ProvincialDivision))
graph.add((current_division, DC.description, Literal(div_name)))
graph.add((current_division, ns_property.dgeqDivisionId, Literal(int(div_id))))
graph.serialize('division.rdf')
def predict(self, s, model_weights, topk=3, maxlen=64):
model = self.network()
model.load_weights(model_weights)
# beam search解码 :每次只保留topk个最优候选结果；如果topk=1，那么就是贪心搜索
xid = np.array([str2id(s, self.char2id)] * topk) # 输入转id
yid = np.array([[2]] * topk) # 解码均以<start>开头，这里<start>的id为2
scores = [0] * topk # 候选答案分数
for i in range(maxlen): # 强制要求输出不超过maxlen字
proba = model.predict([xid,
yid])[:, i,
3:] # 直接忽略<padding>、<unk>、<start>
log_proba = np.log(proba + 1e-6) # 取对数，方便计算
arg_topk = log_proba.argsort(axis=1)[:, -topk:] # 每一项选出topk
_yid = [] # 暂存的候选目标序列
_scores = [] # 暂存的候选目标序列得分
if i == 0:
for j in range(topk):
_yid.append(list(yid[j]) + [arg_topk[0][j] + 3])
_scores.append(scores[j] + log_proba[0][arg_topk[0][j]])
else:
for j in range(topk):
for k in range(topk): # 遍历topk*topk的组合
_yid.append(list(yid[j]) + [arg_topk[j][k] + 3])
_scores.append(scores[j] +
log_proba[j][arg_topk[j][k]])
_arg_topk = np.argsort(_scores)[-topk:] # 从中选出新的topk
_yid = [_yid[k] for k in _arg_topk]
_scores = [_scores[k] for k in _arg_topk]
yid = np.array(_yid)
scores = np.array(_scores)
ends = np.where(yid[:, -1] == 3)[0]
if len(ends) > 0:
k = ends[scores[ends].argmax()]
return id2str(yid[k], self.id2char)
# 如果maxlen字都找不到<end>，直接返回
return id2str(yid[np.argmax(scores)], self.id2char)
def getId(self):
return str2id("%s %s" % (self.name, self.build_number))
def fetch_build_from_file(self, url):
dir_path = self.options.from_file
build_id = str2id(' '.join([i for i in url.split('/') if i][-2:]))
file_path = os.path.join(dir_path, build_id + '.txt')
body = '\n'.join(open(file_path).readlines())
return body
def buildReport(self, bid):
output_dir = self.options.output
if not os.access(output_dir, os.W_OK):
os.mkdir(output_dir, 0775)
bencher = Bencher.getBencherForBid(self.db, self.options, bid)
info = bencher.getInfo(bid)
period = self.period
def_period = int(ceil(info["duration"] / float(self.width))) * 30
bars = 4
plot_type = "linespoints"
plot_type_avg = "lines"
if period is None:
if info["generator"].lower() == "funkload":
cycle_duration = float(info["extra"]["duration"])
# 5 plots by cycle:
period = int(ceil(cycle_duration / 4.0))
plot_type = "impulses"
plot_type_avg = "points"
else:
period = def_period
if 2 * period < def_period:
bars = 2
params = {
"dbpath": self.options.database,
"output_dir": output_dir,
"start": info["start"][11:19],
"end": info["end"],
"bid": bid,
"ravg": self.options.runningavg,
"width": self.width,
"height": self.height,
"period": period,
"duration": info["duration"],
"bars": bars,
"plot_type": plot_type,
"plot_type_avg": plot_type_avg,
}
for sample in [info["all_samples"]] + info["samples"]:
name = sample["name"]
data = bencher.getIntervalInfo(bid, info["start_stamp"], period, name)
data_path = os.path.join(output_dir, str2id(name) + ".data")
f = open(data_path, "w")
for row in data:
row = [i and str(i) or "0" for i in row]
f.write(" ".join(row) + "\n")
f.close()
params["data"] = os.path.basename(data_path)
params["filter"] = " AND lb = '%s' " % name
params["title"] = "Sample: " + sample["title"]
params["filename"] = str2id(name)
if name.lower() == "all":
params["filter"] = ""
params["title"] = "All"
script = render_template("sample-gplot.mako", **params)
script_path = os.path.join(output_dir, str2id(name) + ".gplot")
f = open(script_path, "w")
f.write(script)
f.close()
gnuplot(script_path)
sar = Sar(self.db, self.options)
info.update(sar.getInfo(bid))
for host in info["sar"].keys():
params["host"] = host
params["filter"] = " AND host = '%s'" % host
script = render_template("sar-gplot.mako", **params)
script_path = os.path.join(output_dir, "sar-%s.gplot" % host)
script_path.replace(" ", "-")
f = open(script_path, "w")
f.write(script)
f.close()
gnuplot(script_path)
report = render_template("report.mako", **info)
rst_path = os.path.join(output_dir, "index.rst")
f = open(rst_path, "w")
f.write(report.encode("ascii", "ignore"))
f.close()
html_path = os.path.join(output_dir, "index.html")
generate_html(rst_path, html_path, output_dir)
logging.info("Report generated: " + html_path)
def buildReport(self, bid):
output_dir = self.options.output
if not os.access(output_dir, os.W_OK):
os.mkdir(output_dir, 0775)
bencher = Bencher.getBencherForBid(self.db, self.options, bid)
info = bencher.getInfo(bid)
period = self.period
def_period = int(ceil(info['duration'] / float(self.width))) * 30
bars = 4
plot_type = 'linespoints'
plot_type_avg = 'lines'
if period is None:
if info['generator'].lower() == 'funkload':
cycle_duration = float(info['extra']['duration'])
# 5 plots by cycle:
period = int(ceil(cycle_duration / 4.))
plot_type = 'impulses'
plot_type_avg = 'points'
else:
period = def_period
if 2 * period < def_period:
bars = 2
params = {
'dbpath': self.options.database,
'output_dir': output_dir,
'start': info['start'][11:19],
'end': info['end'],
'bid': bid,
'ravg': self.options.runningavg,
'width': self.width,
'height': self.height,
'period': period,
'duration': info['duration'],
'bars': bars,
'plot_type': plot_type,
'plot_type_avg': plot_type_avg
}
for sample in ([
info['all_samples'],
] + info['samples']):
name = sample['name']
data = bencher.getIntervalInfo(bid, info['start_stamp'], period,
name)
data_path = os.path.join(output_dir, str2id(name) + ".data")
f = open(data_path, 'w')
for row in data:
row = [i and str(i) or '0' for i in row]
f.write(' '.join(row) + '\n')
f.close()
params['data'] = os.path.basename(data_path)
params['filter'] = " AND lb = '%s' " % name
params['title'] = "Sample: " + sample['title']
params['filename'] = str2id(name)
if name.lower() == 'all':
params['filter'] = ''
params['title'] = "All"
script = render_template('sample-gplot.mako', **params)
script_path = os.path.join(output_dir, str2id(name) + ".gplot")
f = open(script_path, 'w')
f.write(script)
f.close()
gnuplot(script_path)
sar = Sar(self.db, self.options)
info.update(sar.getInfo(bid))
for host in info['sar'].keys():
params['host'] = host
params['filter'] = " AND host = '%s'" % host
script = render_template('sar-gplot.mako', **params)
script_path = os.path.join(output_dir, "sar-%s.gplot" % host)
script_path.replace(' ', '-')
f = open(script_path, 'w')
f.write(script)
f.close()
gnuplot(script_path)
report = render_template('report.mako', **info)
rst_path = os.path.join(output_dir, "index.rst")
f = open(rst_path, 'w')
f.write(report.encode('ascii', 'ignore'))
f.close()
html_path = os.path.join(output_dir, "index.html")
generate_html(rst_path, html_path, output_dir)
logging.info('Report generated: ' + html_path)