def __init__(self, sID, onePiece):
today = datetime.date.today()
self.sID = sID
self.opp = onePiece
self.historyDB = Base("F://alfStock//"+"alf123"+'.history')
self.currentDB = Base("F://alfStock//"+"alf123"+'.current')
self.historyDB.open()
self.currentDB.open()
db = Base("F://alfStock//"+str(today)+'.db')
impactDB = Base("F://alfStock//"+str(today)+'.yv')
if db.exists():
db.open()
recs = [ r for r in db if r['sid'] == self.sID ]
if len(recs) > 0:
self.history = recs[0]['history']
self.sCurrent = recs[0]['current']
else:
print "already existed: ", len(db)
self.insertHistory(db)
else:
db.create('sid','history', 'current')
self.insertHistory(db)
if impactDB.exists():
self.idb = impactDB
else:
impactDB.create('sid','UpOrDown')# U:up; D:down
impactDB.open()
impactDB.commit()
self.idb = impactDB
def host():
# show the user profile for that stock
db = Base('overall.db')
db.open()
#stocks = [r for r in db if r['state']==1]
stocks = [r for r in db]
return render_template('all.html', stocks=stocks)
def resetHisDB():
historyDB = Base("F://alfStock//"+"alf123"+'.history')
historyDB.create('sid','Edate', 'length')#Edate := started day not end day
historyDB.open()
historyDB.commit()
currentDB = Base("F://alfStock//"+"alf123"+'.current')
currentDB.create('sid','Edate', 'length')
currentDB.open()
currentDB.commit()
def sell():
# show the user profile for that stock
sm = StockManager()
stock = Stock_Profile('2002')
current = stock.get_result(0)[0]
db = Base('overall.db')
db.open()
stocks = [r for r in db if r['sell']==1 and (r['date']==current)]
return render_template('buy.html', stocks=stocks)
def users():
db = Base('alf.db')
db.open()
users = []
for r in db:
n = r['name']
p = r['pwd']
users.append((n, p))
return render_template('user.html', users=users)
def resetHisDB():
historyDB = Base("F://alfStock//" + "alf123" + '.history')
historyDB.create('sid', 'Edate',
'length') #Edate := started day not end day
historyDB.open()
historyDB.commit()
currentDB = Base("F://alfStock//" + "alf123" + '.current')
currentDB.create('sid', 'Edate', 'length')
currentDB.open()
currentDB.commit()
def alf():
db = Base('alf.db')
db.open()
user = request.form['Username']
pwd = request.form['password']
user_verf = [r['password'] for r in db if r['name'] == user]
if len(user_verf) > 0:
if user_verf[0] == pwd:
return 'Hello, ' + user
else:
return 'Who are you!!!'
class alf123:
def __init__(self, sID, onePiece):
today = datetime.date.today()
self.sID = sID
self.opp = onePiece
self.historyDB = Base("F://alfStock//"+"alf123"+'.history')
self.currentDB = Base("F://alfStock//"+"alf123"+'.current')
self.historyDB.open()
self.currentDB.open()
db = Base("F://alfStock//"+str(today)+'.db')
impactDB = Base("F://alfStock//"+str(today)+'.yv')
if db.exists():
db.open()
recs = [ r for r in db if r['sid'] == self.sID ]
if len(recs) > 0:
self.history = recs[0]['history']
self.sCurrent = recs[0]['current']
else:
print "already existed: ", len(db)
self.insertHistory(db)
else:
db.create('sid','history', 'current')
self.insertHistory(db)
if impactDB.exists():
self.idb = impactDB
else:
impactDB.create('sid','UpOrDown')# U:up; D:down
impactDB.open()
impactDB.commit()
self.idb = impactDB
def insertHistory(self, db):
db.open()
self.history = self.stockHistoryGet()
self.sCurrent = self.stockCurrent()
db.insert(sid = self.sID, history = self.history, current = self.sCurrent)
db.commit()
def TTLUrlOpen(self, url, rc):
retryCount = rc
if retryCount > 2:
pass
else:
try:
response = urllib2.urlopen(url, None, 2.5)
except URLError, e:
print "url"
except socket.timeout:
print "Timed out!"
response = TTLUrlOpen(self, url, retryCount+1)
def getStock(self, sid):
sname = self.dbname(sid)
exist = os.path.isfile(sname)
db = ''
if (exist):
#read db
db = Base(sname)
db.open()
else:
#create a new db
db = Base(sname)
db.create('date','buySig','sellSig', 'state', 'buy', 'sell' ,mode="override")
db.open()
return db
def makeDB(read, write, startTime = "2010-01-01 00:00:00", \
endTime = "2010-01-01 00:10:00"):
db = Base(write)
startTime = calc.datetonumber(startTime)
endTime = calc.datetonumber(endTime)
#Day comes from day of the week. It is a number from 0 to 6.
#0 = Monday 6 = Sunday.
db.create('sensor', 'date', 'weekday', 'index', mode="override")
db.open()
allData = {}
for i in range(len(bbdata.allSensors)):
s = bbdata.allSensors[i]
data = []
print "Parsing sensor " + str(s)
try:
sString = read + "sensor" + str(s) + ".txt"
f = open(sString).readlines()
oldD = None
for timeLine in f:
tmp = timeLine.split()
tmp = tmp[1] + " " + tmp[2]
#tmp = tmp[0] + " " + tmp[1]
d = datetime.datetime.strptime(tmp, "%Y-%m-%d %H:%M:%S")
foo = calc.datetonumber(d)
if foo >= startTime and foo <= endTime:
data.append(calc.datetonumber(d))
if d.toordinal() != oldD:
#Add to database
db.insert(s, d.toordinal(), d.weekday(), len(data) - 1)
oldD = d.toordinal()
print " " + str(d)
except Exception, e:
print "Except:" + str(e)
pass
allData[s] = data
def makeDB(read, write, startTime = "2010-01-01 00:00:00", \
endTime = "2010-01-01 00:10:00"):
db = Base(write)
startTime = calc.datetonumber(startTime)
endTime = calc.datetonumber(endTime)
#Day comes from day of the week. It is a number from 0 to 6.
#0 = Monday 6 = Sunday.
db.create('sensor', 'date', 'weekday', 'index', mode="override")
db.open()
allData = {}
for i in range(len(bbdata.allSensors)):
s = bbdata.allSensors[i]
data = []
print "Parsing sensor " + str(s)
try:
sString = read + "sensor" + str(s) + ".txt"
f = open(sString).readlines()
oldD = None
for timeLine in f:
tmp = timeLine.split()
tmp = tmp[1] + " " + tmp[2]
#tmp = tmp[0] + " " + tmp[1]
d = datetime.datetime.strptime(tmp, "%Y-%m-%d %H:%M:%S")
foo = calc.datetonumber(d)
if foo >= startTime and foo <= endTime:
data.append(calc.datetonumber(d))
if d.toordinal() != oldD:
#Add to database
db.insert(s, d.toordinal(), d.weekday(), len(data) - 1)
oldD = d.toordinal()
print " " + str(d)
except Exception, e:
print "Except:" + str(e)
pass
allData[s] = data
jarfile = 'ark-tweet-nlp-0.3.2.jar'
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s',
level=logging.INFO)
service_url = 'https://www.googleapis.com/freebase/v1/search'
unnecessary = [
'sunday', 'monday', 'tuesday', 'wednesday', 'thursday', 'friday',
'saturday', 'january', 'february', 'march', 'april', 'may', 'june', 'july',
'august', 'september', 'october', 'november', 'december', 'it'
]
freebase_link = 'http://www.freebase.com'
model1 = word2vec.Word2Vec.load_word2vec_format(
'freebase-vectors-skipgram1000-en.bin.gz', binary=True)
chant = enchant.Dict("en_US")
bcluster = Base('bcluster.pdl')
bcluster.open()
api_key = 'AIzaSyAW9RPEnSFbJfGsuVXSiTV_xbMySmJfGMw'
mslink = 'http://weblm.research.microsoft.com/rest.svc/bing-body/2013-12/3/jp?u=4e9af3bb-4cd3-4e29-a10b-e15754d454cb'
#Tokenize and Tag individual tokens using Owoputi et al. tagger
def tokenize():
cmd = 'java -XX:ParallelGCThreads=2 -Xmx500m -jar ' + jarfile + ' \"' + testfile + '\"'
process = subprocess.Popen(cmd,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
shell=True)
return iter(process.stdout.readline, b'')
#Collect ngrams from the segments
class EventPassportOffice:
#what do we need in init?
#pressure run ID number
#acoustic ID number
#(btw marking those separate is a bad idea on the operators part)
def __init__(self):
self.EventPassport = Base('EventPassport/EventPassport.pdl')
#check if the DB exists. If Yes, open, if not
#create it:
if not self.EventPassport.exists():
self.genPDL()
else:
self.EventPassport.open()
self.CleanEvents = CleanEvents.CleanData()
def genPDL(self):
#Create the PDL file for database
self.EventPassport.create('EventID','Temperature','Pressure','Time', 'RunNumber','Path', 'RunType', mode = "open")
#RunNumber is defined as RunNumberAcoustic
#Runtype can be neutron or alpha
def genPassport(self, Path, RunNumberAcoustic, RunNumberPressure, RunType_WS):
FilteredData = self.CleanEvents.MatchEvent_PressurePiezo(Path, str(RunNumberAcoustic), str(RunNumberPressure))
#Get the last EventID
recs = [ Record['EventID'] for Record in self.EventPassport if Record['RunNumber'] == RunNumberAcoustic]
if len(recs) == 0:
EID = str(RunNumberAcoustic)+"0001"
EID = int(EID)
else:
EID = max(recs)+1
#check if we have a duplicate!
for DataPoint in FilteredData:
timestamp = DataPoint[1]
#Check if we have a dupe/conflict
x = [Event for Event in self.EventPassport if Event['Time']-timedelta(seconds=2)<=timestamp<=Event['Time']+timedelta(seconds=2)]
if len(x) == 0:
self.EventPassport.insert(EventID = EID ,Temperature = DataPoint[3],Pressure = DataPoint[2],Time = DataPoint[1], RunNumber = RunNumberAcoustic, Path = DataPoint[0], RunType = RunType_WS)
EID += 1
print("Inserting Entry ...")
else:
print "Duplicate entry found at: "+str(DataPoint[1])+" Event ID: "+str(x[0]['EventID'])
self.EventPassport.commit()
def CheckPassport_RunNumber(self, RunNumberQry):
return self.EventPassport(RunNumber = RunNumberQry)
def CheckPassport_Temperature(self, HighTemp, LowTemp):
return self.EventPassport(HighTemp>Temperature>LowTemp)
def CheckPassport_Time(self, fromTime, toTime):
recs = [ r for r in self.EventPassport if fromTime < r['Time'] < toTime]
return recs
def SizeofPassportDB(self):
return len(self.EventPassport)
def CheckPassport_Runtype(self, runtype_WS):
return self.EventPassport(RunType = runtype_WS)
def CheckPassport_eventID(self, EventID_WS):
return self.EventPassport(EventID = EventID_WS)
def _deleteEvent(self, RecID_WS):
del self.EventPassport[RecID_WS]
self.EventPassport.commit()
class StockManager(object):
def __init__(self):
self.getSummary()
def dbname(self, sid):
return sid + '.db'
def getStock(self, sid):
sname = self.dbname(sid)
exist = os.path.isfile(sname)
db = ''
if (exist):
#read db
db = Base(sname)
db.open()
else:
#create a new db
db = Base(sname)
db.create('date','buySig','sellSig', 'state', 'buy', 'sell' ,mode="override")
db.open()
return db
def updateStock(self, sid, sc):
db = self.getStock(sid)
sdb = self.sdb
if sc['date'] in [r['date'] for r in db]:
pass
else:
db.insert(date = sc['date'],buySig = sc['buySig'],sellSig = sc['sellSig'], state = sc['state'], buy = sc['buy'], sell = sc['sell'])
db.commit()
print '[stock] # ', sid, ' updating'
conflict = [r for r in sdb if ((r['date'] == sc['date']) and (r['stock'] == sid))]
if len(conflict) == 0:
sdb.insert(date = sc['date'], stock = sid ,state = sc['state'], buy = sc['buy'], sell = sc['sell'])
sdb.commit()
print '[summary] creating ', sid
update = [r for r in sdb if ((r['date'] != sc['date']) and (r['stock'] == sid))]
if len(update)>0:
sdb.update(update[0], date = sc['date'], state = sc['state'], buy = sc['buy'], sell = sc['sell'])
sdb.commit()
print '[summary] updating ', sid
def getSummary(self):
self.sdb = Base('overall.db')
self.sdb.open()
return self.sdb
def getCurStatus(self, sid):
db = self.sdb
match = [r for r in db if r['stock'] == sid]
if len(match) == 0:
return 0
else:
return match[0]['state']
def getLatestDate(self, sid):
db = self.sdb
records = [r for r in db if r['stock']==sid]
if len(records) > 0:
return records[0]['date']
else:
return '69/06/19'
class PressureVeto:
#We need the run number for init. We will use PyDBLite
#so we need to gen the db first. There will be another
#function for that. The reason we use this is because
#of native python compatibility
def __init__(self, RunNumber):
#property self.RunNumber assigned.
#This is typecasted to string for manipulation
self.RunNumber = str(RunNumber)
#property self.PyDB -> Database for pressures
self.PyDB = Base('pressures/'+self.RunNumber+'.dbl')
#check if the DB exists. If Yes, open, if not
#create it:
if not self.PyDB.exists():
self.genPDL()
else:
self.PyDB.open()
#Define the time iteration between bubbles minimum threshold
#Remember, each iteration is 1/10th second!
#Iter must be integer!
minSecondsBetweenBubbles = 4
self.minIterBetweenBubbles = int(minSecondsBetweenBubbles*10)
#Funtion to generate PyDBLite database
#I will deliberately not give this MySQL abilities
#since I dont want my data wiped out by "mistake"
#The human veto has to be in here somewhere.
def genPDL(self):
#Create the PDL file for database
self.PyDB.create('id','temp','pressure','time', mode = "override")
#import CSV for CSV file ops. Import ONLY if needed, so its here.
import csv
#filename in CSV file. Assumption -> RunID.csv
fname_csv = self.RunNumber+".csv"
PTcsv = csv.reader(open(fname_csv))
#convert CSV to PyDB line by line
for line in PTcsv:
self.PyDB.insert(id = int(line[0]),temp=float(line[1]), pressure=float(line[2]), time=datetime.strptime(line[3], "%Y-%m-%d %H:%M:%S"))
#Commit the database
self.PyDB.commit()
#Print a confirmation
print "Creating PyDB complete."
#this function finds the "peaks" in the pressures.
#Criterion: Peaks are above 30 PSI
def findBubbleTimings(self):
'''Finds the bubble timings
In -> Pressure data
Out -> Timings (datetime.datetime)
Assumptions -> Bubble PSI > 30 PSI
'''
#Select records with pressure > 30.0 PSI
recs = [r for r in self.PyDB]
#Make an iterator of this list
RecIter = itertools.islice(recs, None)
#Declare memory space for:
#Valid Bubbles
#Temporary Storage
#Last Record's ID (to stop Iterator)
ValidBubbles = []
_VBubbleAmpTemporaryStorage = []
RecLastID = recs[-1:][0]['__id__']
#Go record by record:
for record in RecIter:
#If pressure > 30:
if record['pressure'] >= 30.0:
#Assign the temporary memory with present pressure, time
_VBubbleAmpTemporaryStorage = [record['pressure'], record['time'], record['temp']]
#Number of steps to iter so we dont go beyond the last rec
stepsTillLastRec = RecLastID - record['__id__']
stepsIter = self.minIterBetweenBubbles if ( stepsTillLastRec > self.minIterBetweenBubbles) else stepsTillLastRec
#Investigate for next minIterBetweenBubbles for a maxima
for i in xrange(stepsIter):
#Progress iterator by 1
record = RecIter.next()
#is present iteration > memory stored variable? Yes: Store it, No: Continue
_VBubbleAmpTemporaryStorage = [record['pressure'], record['time'], record['temp']] if record['pressure']>=_VBubbleAmpTemporaryStorage else _VBubbleAmpTemporaryStorage
#The local maxima is found, store it as good data, continue searching
ValidBubbles.append(_VBubbleAmpTemporaryStorage)
#clear the temporary space
_VBubbleAmpTemporaryStorage = []
#Return the time cut!
return ValidBubbles
import enchant
from PyDbLite import Base
import jellyfish
import subprocess
testfile = str(sys.argv[1])
jarfile = 'ark-tweet-nlp-0.3.2.jar'
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
service_url = 'https://www.googleapis.com/freebase/v1/search'
unnecessary = ['sunday','monday','tuesday','wednesday','thursday','friday','saturday','january','february','march','april','may','june','july','august','september','october','november','december','it']
freebase_link = 'http://www.freebase.com'
model1 = word2vec.Word2Vec.load_word2vec_format('freebase-vectors-skipgram1000-en.bin.gz', binary=True)
chant = enchant.Dict("en_US")
bcluster = Base('bcluster.pdl')
bcluster.open()
api_key = 'AIzaSyAW9RPEnSFbJfGsuVXSiTV_xbMySmJfGMw'
mslink = 'http://weblm.research.microsoft.com/rest.svc/bing-body/2013-12/3/jp?u=4e9af3bb-4cd3-4e29-a10b-e15754d454cb'
#Tokenize and Tag individual tokens using Owoputi et al. tagger
def tokenize():
cmd = 'java -XX:ParallelGCThreads=2 -Xmx500m -jar '+jarfile+' \"'+testfile+'\"'
process = subprocess.Popen(cmd,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,shell=True)
return iter(process.stdout.readline, b'')
#Collect ngrams from the segments
def ngrams(input, n):
input = input.split(' ')
class SignalManip:
#usual stuff in init
def __init__(self):
self.AnalysisResults = Base('AnalysisResults/AnalysisResults.pdl')
#check if the DB exists. If Yes, open, if not
#create it:
if not self.AnalysisResults.exists():
self.genPDL()
else:
self.AnalysisResults.open()
self.PassportOffice = EventPassport.EventPassportOffice()
self.LoadWaveform = WaveformLoader.LoadWave()
self.AcousticAnalysis = AnalysisTools.AcousticsAnalysis()
#If DB doesnt exist, make it!
def genPDL(self):
#Create the PDL file for database
self.AnalysisResults.create('EventID','PVar', mode = "open")
#Function to generate signal average
def genSignalAverage(self, EventType = "Neutron"):
#get all Events of type EventType
EventList = []
EventList = self.PassportOffice.CheckPassport_Runtype(EventType)
SignalAvgMem = numpy.zeros((50000))
for Event in EventList:
#Load Raw data
raw_data = self.LoadWaveform.LoadData(Event['Path'][:-3])
SignalAvgMem += raw_data[0]
SignalAvgMem /= len(EventList)
####Storage#####
Storage = open("AnalysisResults/signalAvg."+EventType+".binary", "wb")
SignalAvgMem.tofile(Storage, format="%f")
Storage.close()
return SignalAvgMem
#function to generate FFT avergae
def genFFTAverage(self, EventType="Neutron", doWin = False, winStart=10000, winEnd=30000, Fs = 1250000.0):
#get all Events of type EventType
EventList = []
EventList = self.PassportOffice.CheckPassport_Runtype(EventType)
FFTAvgMem = numpy.zeros((50000))
FFTAvgBins = numpy.fft.fftfreq(len(FFTAvgMem), 1.0/Fs)
for Event in EventList:
#Load Raw data
raw_data = self.LoadWaveform.LoadData(Event['Path'][:-3])
####SignalWindow####
if doWin:
print "is it"
TempSigMem = numpy.zeros((50000))
TempSigMem[winStart:winEnd] = raw_data[0][winStart:winEnd]
R_data = TempSigMem
else:
R_data = raw_data[0]
#
FFTs = numpy.fft.fft(R_data)
#for i in range(5000,6000):
#pwrspec = abs(numpy.mean(FFTs[5000:6000]))
#if pwrspec>10:
# print pwrspec, Event
FFTAvgMem += FFTs
FFTAvgMem /= len(EventList)
####Storage#####
#FFT#
Storage = open("AnalysisResults/FFTAvg."+EventType+"win"+str(doWin)+".binary", "wb")
FFTAvgMem.tofile(Storage, format="%f")
Storage.close()
#FFT FREQS#
Storage = open("AnalysisResults/FFTAvgBins."+EventType+"win"+str(doWin)+".binary", "wb")
FFTAvgBins.tofile(Storage, format="%f")
Storage.close()
####Plotting#####
return FFTAvgMem, FFTAvgBins
#Functions to show the Average values (load from cache)
def getSignalAverage(self, EventType = "Neutron"):
Storage = "AnalysisResults/signalAvg."+EventType+".binary"
if not os.path.exists(Storage):
data = self.genSignalAverage(EventType)
else:
data = numpy.fromfile(Storage)
return data
#function to show average FFT
def getFFTAverage(self, EventType = "Neutron", doWin = False,):
Storage_FFT = "AnalysisResults/FFTAvg."+EventType+"win"+str(doWin)+".binary"
Storage_FFTfreq = "AnalysisResults/FFTAvgBins."+EventType+"win"+str(doWin)+".binary"
#Broken. Needs param check and hassles.
#if os.path.exists(Storage_FFT) and os.path.exists(Storage_FFTfreq) :
# data_FFT = numpy.fromfile(Storage_FFT)
# data_FFTFreq = numpy.fromfile(Storage_FFTfreq)
#else:
# data_FFT, data_FFTFreq = self.genFFTAverage(EventType, doWin)
data_FFT, data_FFTFreq = self.genFFTAverage(EventType, doWin)
return data_FFT, data_FFTFreq
'''
Created on 2014/7/17
@author: USER
'''
from stock_profile import *
from PyDbLite import Base
'''
k = Base('2325.db')
k.open()
for r in k:
print r
'''
one_dream = Base('overall.db')
one_dream.open()
print one_dream.fields
stock = Stock_Profile('2002')
current = stock.get_result(0)[0]
stocks = [r for r in one_dream if (r['buy']==1) and (r['date']==current)]
for s in stocks:
print s['date'], s['buy'], s['stock']
class doAnalysis:
#What do we need in init now? Ah, the analysis cache DB
def __init__(self):
self.AnalysisResults = Base('AnalysisResults/AnalysisResults.pdl')
#check if the DB exists. If Yes, open, if not
#create it:
if not self.AnalysisResults.exists():
self.genPDL()
else:
self.AnalysisResults.open()
self.PassportOffice = EventPassport.EventPassportOffice()
self.LoadWaveform = WaveformLoader.LoadWave()
self.AcousticAnalysis = AnalysisTools.AcousticsAnalysis()
self.SignalManip = SignalManip.SignalManip()
#If DB doesnt exist, make it!
def genPDL(self):
#Create the PDL file for database
self.AnalysisResults.create('EventID','PVar', mode = "open")
#Gen PVAr of the Signals!
def genPVAR(self):
'''
Filter Params.
doFilter -> Filter on or OFF
lowfreq_HP -> Low frequency High Pass
highFreq_LP -> High Frequency low pass
Set both for a band pass filter.
Filter Types:
ApplyFiltersWall -> Boxcar window
ApplyFiltersFIR -> Kaiser Window
'''
doFilter = True
lowFreq_HP = 3000
highFreq_LP = None
####Neutron Data#####
#get the list of events
PVar_Neutron_List = []
EventList = self.PassportOffice.CheckPassport_Runtype("Neutron")
#For every Event
for Event in EventList:
#Load Raw data
raw_data = self.LoadWaveform.LoadData(Event['Path'][:-3])
#Apply filter. See the docstring
#for options
if doFilter:
filtered_data = self.AcousticAnalysis.ApplyFiltersWall(raw_data[0], lowFreq=lowFreq_HP, highFreq=highFreq_LP)
else:
filtered_data = raw_data[0]
#Calculate PVAR
PVar = self.AcousticAnalysis.calculatePVar(filtered_data)
#PVAr > 25 were observed for events from the wall from 1 specific run!
#We dont know what to do with those yet.
#if PVar<20:
PVar_Neutron_List.append(PVar)
##########Plotting#########
hist_bins = numpy.arange(10,13.0,0.1)
#hist_bins=20
plt.hist(PVar_Neutron_List, bins=hist_bins, normed=True, facecolor='green', alpha=0.75)
plt.grid(True)
plt.xlabel("PVar")
plt.ylabel("Count")
plt.title("PVar of Entire Dataset")
#### ALPHA DATA ####
PVar_Alpha_List = []
EventList = self.PassportOffice.CheckPassport_Runtype("Alpha")
for Event in EventList:
#get raw data
raw_data = self.LoadWaveform.LoadData(Event['Path'][:-3])
#Apply filter. See the docstring
#for options
if doFilter:
filtered_data = self.AcousticAnalysis.ApplyFiltersWall(raw_data[0], lowFreq=lowFreq_HP, highFreq=highFreq_LP)
else:
filtered_data = raw_data[0]
PVar = self.AcousticAnalysis.calculatePVar(filtered_data)
PVar_Alpha_List.append(PVar)
########Plotting#######
#print PVar_Alpha_List
plt.hist(PVar_Alpha_List, bins=hist_bins, normed=True, facecolor='red', alpha=0.40)
plt.show()
#Functions to show the Average values (load from cache)
def PlotSignalAverage(self):
#Run 2X to get data for alpha and for neutron
data_neutron = self.SignalManip.getSignalAverage(EventType = "Neutron")
data_alpha = self.SignalManip.getSignalAverage(EventType = "Alpha")
###Plotting###
plt.plot(data_neutron,'g-')
plt.plot(data_alpha,'r-')
plt.xlabel("Timestep")
plt.ylabel("Signal (mv)")
plt.grid(True)
plt.show()
#function to show average FFT
def PlotFFTAverage(self):
#Run 2X to get data for alpha and for neutron
FFTs_neutron, FFTfreqs = self.SignalManip.getFFTAverage(EventType = "Neutron", doWin=False)
FFTs_alpha, FFTfreqs_alpha = self.SignalManip.getFFTAverage(EventType = "Alpha", doWin=False)
#get half length of FFT for plotting
length = len(FFTs_neutron)
halflength = length/2
FFTAvgBins_kHz_HL = FFTfreqs[:halflength]/1000.0
#PLOTTING#
plt.plot(FFTAvgBins_kHz_HL, abs(FFTs_neutron[:halflength]),'g-')
#plt.plot(abs(FFTs_neutron[:halflength]),'g-')
plt.plot(FFTAvgBins_kHz_HL, abs(FFTs_alpha[:halflength]),'r-')
plt.xlabel("Frequency")
plt.ylabel("Count")
plt.title("Average FFT of all signals")
plt.grid(True)
plt.show()
#################
################
################
###THIS FUNCTION IS MY TEST BED AND HAS NO COMMENTS
#Nor do I plan on putting some!!
def _ApplyFilter(self):
PVar_Neutron_List = []
EventList = self.PassportOffice.CheckPassport_Runtype("Neutron")
Loc = EventList[12]['Path'][:-3]
EventList2 = self.PassportOffice.CheckPassport_Runtype("Alpha")
Loc2 = EventList2[12]['Path'][:-3]
raw_dataNeutron = self.LoadWaveform.LoadData('Piezo/triggers.Nov23/trigger_2012.11.23_12.56.15_run_196_110_85')
#raw_dataNeutron = self.LoadWaveform.LoadData(Loc)
raw_dataN = raw_dataNeutron[0]
raw_dataAlpha = self.LoadWaveform.LoadData(Loc2)
raw_dataA = raw_dataAlpha[0]
#r_data = numpy.zeros((50000))
#r_data[13000:20000]=raw_data[13000:20000]
#r_data=raw_data[0]
#raw_data=r_data
SampleTime = raw_dataN[1]
#print 1.0/SampleTime
n = len(raw_dataN)
#filtered_data = self.AcousticAnalysis.ApplyFiltersWall(raw_data, lowFreq=10000, highFreq=None)
#print filtered_data
fftsN = numpy.fft.rfft(raw_dataN)
fftsN = fftsN[:n/2]
fftfreqsN = numpy.fft.fftfreq(len(raw_dataN), 1.0/1250000.0)
fftfreqsN = fftfreqsN[:n/2]
fftsA = numpy.fft.rfft(raw_dataA)
fftsA = fftsA[:n/2]
fftfreqsA = numpy.fft.fftfreq(len(raw_dataA), 1.0/1250000.0)
fftfreqsA = fftfreqsA[:n/2]
#############PLotting##############
plt.title('Data and FFT of Signal')
ax1 = plt.subplot2grid((4,3), (0,0), colspan=3)
ax2 = plt.subplot2grid((4,3), (1,0), colspan=3)
#data
ax1.plot(raw_dataN,'g-')
ax1.set_xlabel('Sample (S.Time = 8e-7s)')
ax1.set_ylabel('Amplitude (mV)')
##### Data INFO
#Low vs High cutoff
plotrange = 10000
plotrange_cutoff = 600
##########
#All
ax2.plot(raw_dataA,'r-')
#ax2.locator_params(axis = 'x',nbins=50)
ax2.set_xlabel('Frequency (kHz)')
##plt.show()
##plt.clf()
#
#
#
#########Plot 2########
ax3 = plt.subplot2grid((4,3), (2,0), colspan=3)
ax4 = plt.subplot2grid((4,3), (3,0), colspan=3)
##Low
ax3.plot(abs(fftN),'g-')
#ax3.plot(fftfreqsN/1000,abs(fftsN),'g-')
#ax3.locator_params(axis = 'x',nbins=50)
#ax3.set_xlabel('Frequency (kHz)')
#ax3.set_ylabel('Count')
##high
ax4.plot(abs(fftsA),'r-')
#ax4.plot(fftfreqsA/1000,abs(fftsA),'r-')
ax4.locator_params(axis = 'x',nbins=50)
ax4.set_xlabel('Frequency (kHz)')
##ax4.set_ylabel('Count')
plt.show()
'''
Created on 2014/6/18
@author: USER
'''
from PyDbLite import Base
db = Base('overall.db')
db.create('date', 'stock', 'state', 'buy', 'sell' ,mode="override")
db.commit()
'''
db.open()
print db.fields
for r in db:
print r['date'], r['state'], r['stock'], r['buy'], r['sell']
'''
