def getLsbChange():
df = ofd.getFilteredData()
isDFempty = df.empty
if isDFempty == True:
print 'No Data Available...'
else:
del df['id']
df = df.set_index(['ts'])
df2 = df.copy()
dfa = []
df3 = df2.resample('30Min').fillna(method='pad')
dfv = df3 - df3.shift(12)
if len(dfa) == 0:
dfa = dfv.copy()
else:
dfa = dfa.append(dfv)
dfa = dfa[pd.notnull(dfa.x)]
dfajson = dfa.reset_index().to_json(orient="records",
date_format='iso')
dfajson = dfajson.replace("T", " ").replace("Z",
"").replace(".000", "")
print dfajson
def getLsbChange():
df = ofd.getFilteredData()
isDFempty = df.empty
if isDFempty == True:
print 'No Data Available...'
else:
del df['id']
df = df.set_index(['ts'])
df2 = df.copy()
dfa = []
df3 = df2.resample('30Min').fillna(method='pad')
dfv = df3 - df3.shift(12)
if len(dfa) == 0:
dfa = dfv.copy()
else:
dfa = dfa.append(dfv)
dfa = dfa[pd.notnull(dfa.x)]
dfajson = dfa.reset_index().to_json(orient="records",date_format='iso')
dfajson = dfajson.replace("T"," ").replace("Z","").replace(".000","")
print dfajson
def GenLsbAlerts():
sites = GetSensorList()
alertTxt = ""
alertTxt2 = ""
print "Getting lsb alerts"
for site in sites:
for nid in range(1, site.nos + 1):
df = ofd.getFilteredData(
isCmd=False,
inSite=site.name,
inNode=nid,
inStart=(dt.now() - td(7)).strftime("%y/%m/%d %H:%M:%S"))
isDFempty = df.empty
if isDFempty == True:
PrintOut('No Data Available... for %s %s' % (site.name, nid))
continue
df = df.set_index(['ts'])
df2 = df.copy()
dfa = []
try:
df3 = df2.resample('30Min').fillna(method='pad')
except pd.core.groupby.DataError:
#print "No data to resample %s %s" % (site.name, nid)
continue
dfv = df3 - df3.shift(12)
if len(dfa) == 0:
dfa = dfv.copy()
else:
dfa = dfa.append(dfv)
window = 48
dfarm = pd.rolling_mean(dfa, window)
dfarm = dfarm[dfarm.index > dt.now() - td(1)]
if (((abs(dfarm.x) > 0.25) | (abs(dfarm.y) > 0.25) |
(abs(dfarm.z) > 1.0)).any()):
ins = "%s,%s" % (site.name, nid)
alertTxt += ins
alertTxt2 += ins
print ins + '\t',
if ((abs(dfarm.x) > 0.25).any()):
print 'x',
alertTxt += ',1'
alertTxt2 += ',' + repr(max(abs(dfarm.x)))
else:
alertTxt += ',0'
alertTxt2 += ',0'
if ((abs(dfarm.y) > 0.25).any()):
print 'y',
alertTxt += ',1'
alertTxt2 += ',' + repr(max(abs(dfarm.y)))
else:
alertTxt += ',0'
alertTxt2 += ',0'
if ((abs(dfarm.z) > 1.0).any()):
print 'z',
alertTxt += ',1'
alertTxt2 += ',' + repr(max(abs(dfarm.z)))
else:
alertTxt += ',0'
alertTxt2 += ',0'
print ''
alertTxt += '\n'
alertTxt2 += '\n'
f = open('lsbalerts.csv', 'w')
f.write(alertTxt)
f.close()
f = open('lsbalerts2.csv', 'w')
f.write(alertTxt2)
f.close()
def GenLsbAlerts():
sites = GetSensorList()
alertTxt = ""
alertTxt2 = ""
print "Getting lsb alerts"
for site in sites:
for nid in range(1, site.nos+1):
df = ofd.getFilteredData(isCmd = False, inSite = site.name, inNode = nid, inStart = (dt.now()-td(7)).strftime("%y/%m/%d %H:%M:%S"))
isDFempty = df.empty
if isDFempty == True:
PrintOut('No Data Available... for %s %s' % (site.name, nid))
continue
df = df.set_index(['ts'])
df2 = df.copy()
dfa = []
try:
df3 = df2.resample('30Min').fillna(method='pad')
except pd.core.groupby.DataError:
#print "No data to resample %s %s" % (site.name, nid)
continue
dfv = df3 - df3.shift(12)
if len(dfa) == 0:
dfa = dfv.copy()
else:
dfa = dfa.append(dfv)
window = 48
dfarm = pd.rolling_mean(dfa, window)
dfarm = dfarm[dfarm.index > dt.now()-td(1)]
if (((abs(dfarm.x)>0.25) | (abs(dfarm.y)>0.25) | (abs(dfarm.z)>1.0)).any()):
ins = "%s,%s" % (site.name, nid)
alertTxt += ins
alertTxt2 += ins
print ins + '\t',
if ((abs(dfarm.x)>0.25).any()):
print 'x',
alertTxt += ',1'
alertTxt2 += ',' + repr(max(abs(dfarm.x)))
else:
alertTxt += ',0'
alertTxt2 += ',0'
if ((abs(dfarm.y)>0.25).any()):
print 'y',
alertTxt += ',1'
alertTxt2 += ',' + repr(max(abs(dfarm.y)))
else:
alertTxt += ',0'
alertTxt2 += ',0'
if ((abs(dfarm.z)>1.0).any()):
print 'z',
alertTxt += ',1'
alertTxt2 += ',' + repr(max(abs(dfarm.z)))
else:
alertTxt += ',0'
alertTxt2 += ',0'
print ''
alertTxt += '\n'
alertTxt2 += '\n'
f = open('lsbalerts.csv', 'w')
f.write(alertTxt)
f.close()
f = open('lsbalerts2.csv', 'w')
f.write(alertTxt2)
f.close()
def getDF():
site = sys.argv[1]
#time start
timeStart = (dt.now()-td(2)).strftime("%y/%m/%d %H:%M:%S")
timeEnd = (dt.now()).strftime("%y/%m/%d %H:%M:%S")
timeTarget = (dt.now()-td(days=1,hours=6)).strftime("%Y-%m-%d %H:%M:%S")
#print "End Time: " + timeEnd + ", Target Time: " + timeTarget
#get the max number of nodes for the site
engineRaw = create_engine('mysql+mysqldb://updews:[email protected]/senslopedb')
query = "SELECT num_nodes FROM site_column_props WHERE name = '%s'" % (site)
results = pd.io.sql.read_sql(query,engineRaw)
maxNode = int(results.ix[0]["num_nodes"])
allNodes = []
for num in range(1, maxNode):
#print "current node: %d" % (num)
#Changed date difference is 1 day or 24 hours
df = ofd.getFilteredData(isCmd = False, inSite = site, inNode = num, inStart = timeTarget)
if df.empty:
#for times that there are no data for the specific node
continue
#site should be "id". Its only "site" temporarily...
df.columns = ['timestamp','site','xalert','yalert','zalert']
df = df.set_index(['timestamp'])
df2 = df.copy()
dfa = []
df3 = df2.resample('30Min').fillna(method='pad')
#dfv = df3 - df3.shift(12)
dfv = df3.copy()
dfv.xalert = abs(df3.xalert - df3.xalert.shift(12))
dfv.yalert = abs(df3.yalert - df3.yalert.shift(12))
dfv.zalert = abs(df3.zalert - df3.zalert.shift(12))
#Enable this for debugging
#print dfv
if len(dfa) == 0:
dfa = dfv.copy()
else:
dfa = dfa.append(dfv)
dfa = dfa[pd.notnull(dfa.xalert)]
if len(allNodes) == 0:
allNodes = dfa.copy()
else:
allNodes = allNodes.append(dfv)
allNodes = allNodes[pd.notnull(allNodes.xalert)]
allNodes = allNodes[allNodes.index > dt.now()-td(hours=24, minutes=0)]
dfajson = allNodes.reset_index().to_json(orient="records",date_format='iso')
dfajson = dfajson.replace("T"," ").replace("Z","").replace(".000","")
print dfajson
def getDF():
site = sys.argv[1]
#time start
timeStart = (dt.now() - td(2)).strftime("%y/%m/%d %H:%M:%S")
timeEnd = (dt.now()).strftime("%y/%m/%d %H:%M:%S")
timeTarget = (dt.now() - td(days=1, hours=6)).strftime("%Y-%m-%d %H:%M:%S")
#print "End Time: " + timeEnd + ", Target Time: " + timeTarget
#get the max number of nodes for the site
engineRaw = create_engine(
'mysql+mysqldb://updews:[email protected]/senslopedb')
query = "SELECT num_nodes FROM site_column_props WHERE name = '%s'" % (
site)
results = pd.io.sql.read_sql(query, engineRaw)
maxNode = int(results.ix[0]["num_nodes"])
allNodes = []
for num in range(1, maxNode):
#print "current node: %d" % (num)
#Changed date difference is 1 day or 24 hours
df = ofd.getFilteredData(isCmd=False,
inSite=site,
inNode=num,
inStart=timeTarget)
if df.empty:
#for times that there are no data for the specific node
continue
#site should be "id". Its only "site" temporarily...
df.columns = ['timestamp', 'site', 'xalert', 'yalert', 'zalert']
df = df.set_index(['timestamp'])
df2 = df.copy()
dfa = []
df3 = df2.resample('30Min').fillna(method='pad')
#dfv = df3 - df3.shift(12)
dfv = df3.copy()
dfv.xalert = abs(df3.xalert - df3.xalert.shift(12))
dfv.yalert = abs(df3.yalert - df3.yalert.shift(12))
dfv.zalert = abs(df3.zalert - df3.zalert.shift(12))
#Enable this for debugging
#print dfv
if len(dfa) == 0:
dfa = dfv.copy()
else:
dfa = dfa.append(dfv)
dfa = dfa[pd.notnull(dfa.xalert)]
if len(allNodes) == 0:
allNodes = dfa.copy()
else:
allNodes = allNodes.append(dfv)
allNodes = allNodes[pd.notnull(allNodes.xalert)]
allNodes = allNodes[allNodes.index > dt.now() - td(hours=23, minutes=30)]
dfajson = allNodes.reset_index().to_json(orient="records",
date_format='iso')
dfajson = dfajson.replace("T", " ").replace("Z", "").replace(".000", "")
print dfajson