def eval_predict(prices, checkpoints, bars_later, expect):
result = list()
for N in checkpoints:
if prices[N + bars_later] >= prices[N] * expect:
result.append(1)
else:
result.append(0)
return result
def find_new_high(granularity, range_down, range_up, bars, correction_bars,
exchange):
pairs = read_coin_pair(granularity, exchange)
result = list()
for fsym, tsym in pairs:
X = get_X(fsym, tsym, granularity, exchange)
highs = get_high(X)
h = REF(highs, 1)
hh = HHV(highs[1:], bars)
hhb = HHVBARS(highs[1:], bars)
if (h >= hh * range_down) & (h <= hh * range_up) & (hhb >
correction_bars):
result.append([fsym, tsym, hh, h])
return np.array(result)
def parsePageUrl (self,page):
soup = BeautifulSoup(page)
print "title==>",soup.title.string
if "登录中心 － 支付宝" in soup.title.string:
return False
hrefs = soup.find_all('td', {'class': "detail-link"})#
#hrefs = soup.find_all('a', {'seed': re.compile('detailLink-linkT*')})
print "==>",hrefs
result = []
for href in hrefs:
result.append(href.find("a")['href'])
print "-->",href,"===",href.find("a"),"---",href.find("a")['href']
return result
def dowith():
result=[]
csvfile=file('E:\\编程\\数字\\llll.csv','rb')
reader=csv.reader(csvfile)
csvfile = file('E:\\编程\\数字\\lllll.csv', 'wb')
writer = csv.writer(csvfile)
i=1
for line in reader:
result.append((i,line[0][0]))
i=i+1
writer.writerows(result)
def showAllRegistryTag(registry_ip,registry_port):
try:
r=requests.get('http://'+registry_ip+":"+registry_port+"/v1/search?q=",timeout=5)
if r.status_code==200:
result=[]
re=r.json()
repos=re['results']
for repo in repos:
r=requests.get('http://'+registry_ip+":"+registry_port+"/v1/repositories/"+repo['name']+"/tags",timeout=5)
re=r.json()
for k,v in re.items():
t={}
t['name']=repo['name']
t['tag']=k
t['image_id']=v
result.append(t)
return result
except Exception:
return
def macd_crossover(close, fast, slow, signal):
result = list()
close = np.array([float(i) for i in close])
macd, macdsignal, macdhist = talib.MACD(close,
fastperiod=fast,
slowperiod=slow,
signalperiod=signal)
if (len(macdhist)) >= (slow + signal -
1): #ensure macdhist is mature enough
for N in range(len(macdhist) - 1):
if (macdhist[N + 1] >= 0) & (macdhist[N] < 0):
result.append(N)
# result.append((N,'gold'))
# elif (macdhist[-(N+2)] >= 0) & (macdhist[-(N+1)] < 0):
# result.append((N,'dead'))
return result
def showAllRegistryTag(registry_ip, registry_port):
try:
r = requests.get('http://' + registry_ip + ":" + registry_port +
"/v1/search?q=",
timeout=5)
if r.status_code == 200:
result = []
re = r.json()
repos = re['results']
for repo in repos:
r = requests.get('http://' + registry_ip + ":" +
registry_port + "/v1/repositories/" +
repo['name'] + "/tags",
timeout=5)
re = r.json()
for k, v in re.items():
t = {}
t['name'] = repo['name']
t['tag'] = k
t['image_id'] = v
result.append(t)
return result
except Exception:
return
def classify(train_images,test_images,num_list,n):
train_images=changeImage(train_images)
test_images=changeImage(test_images)
train_images=numpy.array(train_images)
test_images=numpy.array(test_images)
result=[]
listnum=0
for test_line in test_images:
poor=train_images-test_line
sqr=poor**2
sqDistance=sqr.sum(axis=1)
distance=sqDistance**0.5
sortedDistIndicies=distance.argsort()
classCount={}
for i in range(n):
index=num_list[sortedDistIndicies[i]]
classCount[index]=classCount.get(index,0)+1
sortedClassCount=sorted(classCount.iteritems(),key=operator.itemgetter(1),reverse=True)
result.append([sortedClassCount[0][0]])
print listnum,':\n'
print sortedClassCount[0][0]
print '\n'
listnum+=1
return result
