def convert_to_utc(time, user):
try:
tz = pytz.timezone(user.sciriususer.timezone)
except:
return time
return tz.normalize(tz.localize(time.replace(tzinfo=None))).astimezone(
pytz.utc)
def read_csv(fname):
from csv import DictReader, excel
results = []
dialect = excel()
dialect.skipinitialspace = True
lines = open(fname).readlines()
header = DictReader(lines[0:2], dialect=dialect).next()
device = header["Service Account"]
data = DictReader(lines[3:], dialect=dialect)
for datum in data:
time = datetime.strptime(datum["Interval Date & Time"],
"%m/%d/%Y %I:%M %p ")
time = time.replace(tzinfo=timezone("America/Los_Angeles"))
results.append({
"device": "sce-" + device,
"sensor": "meter",
"type": "mains",
"time": to_epoch(time),
"duration": 3600,
"value": float(datum["kWh Delivered"])
})
return results
def read_xml(fname, device):
from xml.etree import ElementTree
results = []
tree = ElementTree.parse(fname)
for interval in tree.getroot().findall(
".//{http://www.w3.org/2005/Atom}IntervalReading"):
period = interval.find("{http://www.w3.org/2005/Atom}timePeriod")
time = datetime.utcfromtimestamp(
int(period.find("{http://www.w3.org/2005/Atom}start").text))
time = time.replace(tzinfo=timezone("America/Los_Angeles"))
results.append({
"device":
"sce-" + device,
"sensor":
"meter",
"type":
"mains",
"time":
to_epoch(time),
"duration":
int(period.find("{http://www.w3.org/2005/Atom}duration").text),
"value":
float(interval.find("{http://www.w3.org/2005/Atom}value").text)
})
return results
def test_standup_start():
clear()
info2 = auth_register("*****@*****.**", "RFVtgb45678", "M", "Johnson")
channels_create(info2['token'], 'first', True)
time = datetime.utcnow() + timedelta(seconds=6)
assert standup_start(info2['token'], 0, 6) == {
'time_finish': round(time.replace(tzinfo=timezone.utc).timestamp(), 0),
}
def request_newsUrl(self, url, type_cn, date):
ls = []
res = requests.get(url)
res_soup = bs(res.content, 'html.parser')
contents = res_soup.select('div.newslist-container > a')
for j in contents:
time = j.select('span.newstime')[0].get_text()
time = time.replace('/', '-')
time = re.search('[0-9]+-[0-9]+-[0-9]+', time).group(0)
if date == 'all' or time in date:
href = j.attrs['href']
title = j.attrs['title']
ls.append({'date': time, 'url': href, 'title': title})
return ls
def read_html(fname):
from xml.etree import ElementTree
results = []
tree = ElementTree.parse(fname)
table = tree.getroot().find(
".//{http://www.w3.org/1999/xhtml}table[@id='gvRawDataByDevice']")
headings = [
th.text
for th in table.find("{http://www.w3.org/1999/xhtml}tr").findall(
"{http://www.w3.org/1999/xhtml}th")
]
def make_dict(rows):
for row in rows:
cells = [
c.text for c in row.findall("{http://www.w3.org/1999/xhtml}td")
]
if len(cells) == 0:
continue
yield dict(zip(headings, cells))
data = make_dict(table.findall("{http://www.w3.org/1999/xhtml}tr"))
for datum in data:
time = datetime.strptime(datum["Measured Date (30 min)"],
"%m/%d/%Y %I:%M:%S %p")
time = time - timedelta(seconds=time.second)
time = time.replace(tzinfo=timezone("America/Los_Angeles"))
results.append({
"device": "solarcity-" + datum["InverterID"],
"sensor": "generated",
"type": "solar",
"time": to_epoch(time),
"duration": 15 * 60,
"value": float(datum["Energy (kWh AC)"])
})
return results
def getEPG(self, chid, dt = None):
self.initTimeFix()
if dt == None:
dt = time.replace(0, 0, 0)
response = self._request('get_epg', 'cid=%s&from_uts=%s&hours=24&time_shift=%s' % (chid, dt, self.timeshift))
res = []
for channel in response['channels']:
if 'time_shift' in channel:
ts_fix = int(channel["time_shift"])*60
else:
ts_fix = self.timeshift *3600
for epg in channel['epg']:
res.append({
'title': epg['title'],
'time': self.fixTime(int(epg['begin']), ts_fix),
'uts': int(epg['begin']),
'info': epg['info'],
'is_video': 0
})
return res
def getEPG(self, chid, dt = None):
self.initTimeFix()
if dt == None:
dt = time.replace(0, 0, 0)
response = self._request('get_epg', 'cid=%s&from_uts=%s&hours=24&time_shift=%s' % (chid, dt, self.timeshift))
res = []
for channel in response['channels']:
if 'time_shift' in channel:
ts_fix = int(channel["time_shift"])*60
else:
ts_fix = self.timeshift *3600
for epg in channel['epg']:
res.append({
'title': epg['title'],
'time': self.fixTime(int(epg['begin']), ts_fix),
'uts': int(epg['begin']),
'info': epg['info'],
'is_video': 0
})
return res
def net_plot(title, AAT, theta, Z, r, lambda_A, lambda_R, layout='fruchterman', plotting = True, graphScale=1.0, color_threshold=0.7, *args, **kwargs):
"""Provide the eigenvector covariances AAT from RESCAL_ALS output
and Z the sampled network from one of the netCreate sampling algorithms
"""
# get system time to name figures
time = str(dt.datetime.now().time())
time = time.replace(':','')
time = time.replace('.','')
# heatmap
hm = ncFunctions.heatmap(AAT, plotting=plotting, color_threshold=color_threshold)
if plotting:
plt.suptitle(r'A(A^T) HAC for Induced Rank = %s, $\lambda_{A}$ = %s, $\lambda_{R}$ = %s ' %(r,lambda_A, lambda_R), fontweight='bold', fontsize=14)
plt.savefig(title+'_heatmap_'+time, figsize=(6,6))
# NETWORK
# Create networkx graph from Z
g = nx.Graph()
#add nodes with colors of group
for n in np.arange(np.shape(hm['corder'])[0]-1):
g.add_node(hm['corder'][n],color=hm['group'][n])
nodeColorList = list(nx.get_node_attributes(g,'color').values())
#add edges with weight of theta (probability the link exists)
cardE = len(np.where(Z==1)[1])
edgeList = [(np.where(Z==1)[0][i], np.where(Z==1)[1][i]) for i in np.arange(cardE)]
edgeWeightList = theta[np.where(Z==1)] * (2 / max(theta[np.where(Z==1)])) #scaled link prob Pr(Z[i,j]=1) * weight
for e in np.arange(len(edgeList)-1):
g.add_edge(edgeList[e][0],edgeList[e][1],weight=edgeWeightList[e])
# NODE SIZES
# 1. cluster linkage importance
#nodesizelist = cluster['linkage'] * (400 / max(cluster['linkage']))
# 2. betweenness centrality (wide range of sizes; very small on periphery)
#nodesizelist = np.asarray(list(nx.betweenness_centrality(G,normalized=False).values())) * (400 / max(list(nx.betweenness_centrality(G,normalized=False).values())))
# 3. degree (smaller range of sizes; easier to see on the periphery)
nodeSizeList = np.asarray(list(g.degree().values())) * (300 / max(list(g.degree().values()))) #scaled so the largest is size 350
# reproducibility
np.random.seed(1)
#bc = nx.betweenness_centrality(g)
E = len(nx.edges(g))
V = len(g)
k = round(E/V,3)
#size = np.array(list(bc.values())) * 1000
# here replacing the hierarchical magnitude hm['corder']
fignx = plt.figure(figsize=(6,6))
## use heatmap color groupings to color nodes and heatmap magnitudes to size nodes
if layout == 'spring':
nx.draw(g, pos=nx.spring_layout(g, scale=graphScale),
node_color=nodeColorList, node_size=nodeSizeList,
width=edgeWeightList)
elif layout == 'fruchterman':
nx.draw(g, pos=nx.fruchterman_reingold_layout(g, scale=graphScale),
node_color=nodeColorList, node_size=nodeSizeList,
width=edgeWeightList)
else:
print('Please indicate at a valid layout.')
#else:
#nx.graphviz_layout(g, prog=graphProg)
plt.title('Network Created from Induced Rank = %s \n V = %s, E = %s, <k> = %s'%(r,V,E,k), fontweight='bold', fontsize=14)
plt.savefig(title+'_graph_'+time, figsize=(6,6))
#plot log degree sequence
degree_sequence=sorted(nx.degree(g).values(),reverse=True)
fig3 = plt.figure(figsize=(5,3))
plt.loglog(degree_sequence)
plt.title('Log Degree Distribution', fontweight='bold', fontsize=14)
return {'cluster':hm, 'graph':g, 'linkage':hm['linkage'], 'group':hm['group']}
def timeStartEnd(time, instrument, interval):
# 夜盘品种
if instrument in ['rb', 'j', 'i', 'jm']:
# 夜盘品种，先解决tradeday
if time.hour >= 21 and time.hour <= 23:
# 周五晚上
if time.weekday() == 4:
tradeday = (time + timedelta(days=2, hours=5)).replace(hour=0)
else:
tradeday = (time + timedelta(hours=5)).replace(hour=0)
elif time.hour < 3:
# 周六凌晨
if time.weekday() == 5:
tradeday = (time + timedelta(days=2, hours=5)).replace(hour=0)
else:
tradeday = (time + timedelta(hours=5)).replace(hour=0)
elif time.hour >= 9 and time.hour <= 15:
tradeday = time.replace(hour=0)
else:
print('输入的时间不在交易范围之内，请检查')
# 日盘品种
else:
tradeday = time.replace(hour=9)
# 解决start 和 end的问题
# 1分钟K线采用闭开区间定义start 和 end
tradeday = tradeday.replace(second=0, microsecond=0)
if interval == INTERVAL_1M:
timestart = time.replace(second=0, microsecond=0)
timeend = timestart + timedelta(minutes=1)
return timestart, timeend, tradeday
elif interval == INTERVAL_5M:
minstart = math.floor(time.minute / 5) * 5
timestart = time.replace(minute=minstart)
timeend = timestart + timedelta(minutes=4, seconds=59)
return timestart, timeend, tradeday
elif interval == INTERVAL_15M:
minstart = math.floor(time.minute / 15) * 15
timestart = time.replace(minute=minstart)
timeend = timestart + timedelta(minutes=14, seconds=59)
return timestart, timeend, tradeday
elif interval == INTERVAL_30M:
minstart = math.floor(time.minute / 30) * 30
timestart = time.replace(minute=minstart)
timeend = timestart + timedelta(minutes=29, seconds=59)
# 30分钟的K线起始终止时间节点，要代替一下
if timeend.hour == 10 and timeend.minute == 29:
timeend = timeend.replace(minute=14)
return timestart, timeend, tradeday
# 60分钟这里
elif interval == INTERVAL_60M:
timestart = time.replace(minute=0)
timeend = timestart + timedelta(minutes=59, seconds=59)
# 30分钟的K线起始终止时间节点，要代替一下
if timeend.hour == 11 and timeend.minute == 59:
timeend = timeend.replace(minute=29)
elif timeend.hour == 2 and timeend.minute == 59:
timeend = timeend.replace(minute=29)
elif timeend.hour == 23 and timeend.minute == 59:
# 晚上23点的这个，很麻烦，之前大商所是凌晨1点闭市，之后改为晚上23点半闭市
if instrument == 'j':
if time.strftime('%Y-%m-%d') >= '2015-05-08':
timeend = timeend.replace(minute=29)
return timestart, timeend, tradeday
elif interval == INTERVAL_1D:
# 夜盘品种
timeend = tradeday.replace(hour=14, minute=59, second=59)
# 夜盘品种
if instrument in ['rb', 'j', 'i', 'jm']:
if time.hour >= 21 and time.hour <= 23:
timestart = time.replace(hour=21)
elif time.hour < 3:
timestart = (time - timedelta(hours=5)).replace(hour=21)
# 如果是夜盘品种，但是前一天没有数据，那么默认假日模式，
elif time.hour >= 9 and time.hour <= 15:
if time.weekday() == 0:
timestart = (time - timedelta(days=3)).replace(hour=21)
else:
timestart = (time - timedelta(days=1)).replace(hour=21)
else:
print('输入的时间不在交易范围之内，请检查')
# 日盘品种
else:
timestart = time.replace(hour=9)
else:
print('输入的时间周期有误，请重新输入')
return timestart, timeend, tradeday
class Chifoumi:
scores = {}
options = ['Rock', 'Paper', 'Scissors']
# prepare file to save sessions & scores
f = open('chifoumi_scores.txt', 'a+')
with open('chifoumi_scores.txt') as my_file:
my_file.seek(0)
first_char = my_file.read(1)
if not first_char:
# the file is empty
f.write('<Player> <Score> <Time in seconds>\n')
f.write('Standard 0 0\n')
else:
my_file.seek(0)
next(my_file)
for line in my_file:
(name, score, time) = line.split(" ")
time = time.replace('\n', '')
scores[name] = list((int(score), float(time)))
def __init__(self, player_name, num_rounds):
self.name = player_name
self.n = num_rounds
if self.name not in self.scores:
self.scores[self.name] = [0, 0]
def start_game(self):
''' start the game '''
start = time()
conteur = 0
i = 0
while i < self.n:
while True:
try:
choice = int(
input("\nRock: 0, Papre: 1, Scissors: 2 ==> "))
break
except ValueError:
print("\nPlease Choose 0, 1 or 2... Play Again!!")
if choice in [0, 1, 2]:
player_1 = self.options[choice]
computer = self.options[randint(0, 2)]
if player_1 == computer:
print('\n*** Tie!! ***')
elif player_1 == "Rock":
if computer == "Paper":
print("\n*** You lose!", computer, "covers", player_1,
"***")
else:
print("\n*** You win!", player_1, "smashes", computer,
"***")
conteur += 1
elif player_1 == "Paper":
if computer == "Scissors":
print("\n*** You lose!", computer, "cut", player_1,
"***")
else:
print("\n*** You win!", player_1, "covers", computer,
"***")
conteur += 1
elif player_1 == "Scissors":
if computer == "Rock":
print("\n*** You lose...", computer, "smashes",
player_1, "***")
else:
print("\n*** You win!", player_1, "cut", computer,
"***")
conteur += 1
else:
print("\nThat's not a valid play. Check your spelling! ")
i += 1
else:
print("\nPlease Choose 0, 1 or 2... Play Again!!")
self.duree = float(time() - start)
self.score = conteur
# to save the highest score
if conteur > self.scores[self.name][0]:
self.scores[self.name][0] = conteur
self.scores[self.name][1] = self.duree
@classmethod
def save_score(cls):
''' saving score to the file '''
cls.f.seek(0)
cls.f.truncate()
cls.f.write('<Player> <Score> <Time in seconds>\n')
for i in cls.scores.keys():
cls.f.write("{} {} {}\n".format(i, cls.scores[i][0],
cls.scores[i][1]))
@classmethod
def rankOfPlayers(cls):
''' Ranking players by score '''
listofTuples = sorted(cls.scores.items(),
key=lambda x: x[1],
reverse=True)
print("\n*************")
print("\nRanking:\n")
for elem in listofTuples:
print(elem[0], " ==> ", elem[1][0])
def net_plot(title,
AAT,
theta,
Z,
r,
lambda_A,
lambda_R,
layout='fruchterman',
plotting=True,
graphScale=1.0,
color_threshold=0.7,
*args,
**kwargs):
"""Provide the eigenvector covariances AAT from RESCAL_ALS output
and Z the sampled network from one of the netCreate sampling algorithms
"""
# get system time to name figures
time = str(dt.datetime.now().time())
time = time.replace(':', '')
time = time.replace('.', '')
# heatmap
hm = ncFunctions.heatmap(AAT,
plotting=plotting,
color_threshold=color_threshold)
if plotting:
plt.suptitle(
r'A(A^T) HAC for Induced Rank = %s, $\lambda_{A}$ = %s, $\lambda_{R}$ = %s '
% (r, lambda_A, lambda_R),
fontweight='bold',
fontsize=14)
plt.savefig(title + '_heatmap_' + time, figsize=(6, 6))
# NETWORK
# Create networkx graph from Z
g = nx.Graph()
#add nodes with colors of group
for n in np.arange(np.shape(hm['corder'])[0] - 1):
g.add_node(hm['corder'][n], color=hm['group'][n])
nodeColorList = list(nx.get_node_attributes(g, 'color').values())
#add edges with weight of theta (probability the link exists)
cardE = len(np.where(Z == 1)[1])
edgeList = [(np.where(Z == 1)[0][i], np.where(Z == 1)[1][i])
for i in np.arange(cardE)]
edgeWeightList = theta[np.where(Z == 1)] * (2 / max(
theta[np.where(Z == 1)])) #scaled link prob Pr(Z[i,j]=1) * weight
for e in np.arange(len(edgeList) - 1):
g.add_edge(edgeList[e][0],
edgeList[e][1],
weight=edgeWeightList[e])
# NODE SIZES
# 1. cluster linkage importance
#nodesizelist = cluster['linkage'] * (400 / max(cluster['linkage']))
# 2. betweenness centrality (wide range of sizes; very small on periphery)
#nodesizelist = np.asarray(list(nx.betweenness_centrality(G,normalized=False).values())) * (400 / max(list(nx.betweenness_centrality(G,normalized=False).values())))
# 3. degree (smaller range of sizes; easier to see on the periphery)
nodeSizeList = np.asarray(list(g.degree().values())) * (300 / max(
list(g.degree().values()))) #scaled so the largest is size 350
# reproducibility
np.random.seed(1)
#bc = nx.betweenness_centrality(g)
E = len(nx.edges(g))
V = len(g)
k = round(E / V, 3)
#size = np.array(list(bc.values())) * 1000
# here replacing the hierarchical magnitude hm['corder']
fignx = plt.figure(figsize=(6, 6))
## use heatmap color groupings to color nodes and heatmap magnitudes to size nodes
if layout == 'spring':
nx.draw(g,
pos=nx.spring_layout(g, scale=graphScale),
node_color=nodeColorList,
node_size=nodeSizeList,
width=edgeWeightList)
elif layout == 'fruchterman':
nx.draw(g,
pos=nx.fruchterman_reingold_layout(g, scale=graphScale),
node_color=nodeColorList,
node_size=nodeSizeList,
width=edgeWeightList)
else:
print('Please indicate at a valid layout.')
#else:
#nx.graphviz_layout(g, prog=graphProg)
plt.title(
'Network Created from Induced Rank = %s \n V = %s, E = %s, <k> = %s'
% (r, V, E, k),
fontweight='bold',
fontsize=14)
plt.savefig(title + '_graph_' + time, figsize=(6, 6))
#plot log degree sequence
degree_sequence = sorted(nx.degree(g).values(), reverse=True)
fig3 = plt.figure(figsize=(5, 3))
plt.loglog(degree_sequence)
plt.title('Log Degree Distribution', fontweight='bold', fontsize=14)
return {
'cluster': hm,
'graph': g,
'linkage': hm['linkage'],
'group': hm['group']
}
def get_writer(command, time, result_dir):
filename = "%s_%s.csv" % (command, time.replace(":", ""))
if result_dir:
filename = join(result_dir, filename)
return csv.writer(open(filename, "w"))
