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load_dataset.py
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load_dataset.py
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"""
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with this work for additional information
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
"""
import pandas
from datetime import datetime
import time
import numpy as np
from keras.preprocessing.text import one_hot
def buildOHE(index,n):
L=[0]*n
L[index]=1
return L
def load_dataset(name):
if name=="HELPDESK17":
return _load_dataset_name("data/Helpdesk2017_anonimyzed.csv")
elif name=="BPI12":
return _load_dataset_name("data/BPI_12_anonimyzed.csv")
elif name == "BPI12OEA":
return _load_dataset_name("data/BPI_12_oneEndAct_anonymized.csv")
elif name=="BPI14":
return _load_dataset_name("data/BPI_14_anonimyzed.csv")
def _load_dataset_name(filename):
dataframe = pandas.read_csv(filename, header=0)
dataframe = dataframe.replace(r's+', 'empty', regex=True)
dataframe = dataframe.fillna(0)
#print dataframe.dtypes
#print dataframe.select_dtypes(['float64','int64'])
dataset=dataframe.values
#print dataset[0]
#dataset=dataset[:,:8]
values = []
for i in range(dataset.shape[1]):
values.append(len(np.unique(dataset[:, i])) )#+1
#print values
#exit(1)
#print np.unique(dataset[:, 5])
elems_per_fold = int(values[0] / 3)
print "DEBUG: elemns per fold",elems_per_fold
datasetTR = dataset[dataset[:,0]<2*elems_per_fold]
#test set
datasetTS = dataset[dataset[:,0]>=2*elems_per_fold]
#trick empty column siav log
#datasetTR=datasetTR[:,:8]
#datasetTS=datasetTS[:,:8]
#print len(values)
#print dataset[0]
def generate_set(dataset):
data=[]
newdataset=[]
temptarget=[]
#analyze first dataset line
caseID=dataset[0][0]
event=dataset[0][1]
starttime=datetime.fromtimestamp(time.mktime(time.strptime(dataset[0][2], "%Y-%m-%d %H:%M:%S")))
lastevtime=datetime.fromtimestamp(time.mktime(time.strptime(dataset[0][2], "%Y-%m-%d %H:%M:%S")))
t=time.strptime(dataset[0][2], "%Y-%m-%d %H:%M:%S")
midnight = datetime.fromtimestamp(time.mktime(t)).replace(hour=0, minute=0, second=0, microsecond=0)
timesincemidnight = (datetime.fromtimestamp(time.mktime(t)) - midnight).total_seconds()
n=1
temptarget.append(datetime.fromtimestamp(time.mktime(time.strptime(dataset[0][2], "%Y-%m-%d %H:%M:%S"))))
a=[(datetime.fromtimestamp(time.mktime(time.strptime(dataset[0][2], "%Y-%m-%d %H:%M:%S")))-starttime).total_seconds() ]
a.append((datetime.fromtimestamp(time.mktime(time.strptime(dataset[0][2], "%Y-%m-%d %H:%M:%S")))-lastevtime).total_seconds() )
a.append(timesincemidnight)
a.append(datetime.fromtimestamp(time.mktime(t)).weekday()+1)
a.extend(buildOHE(one_hot(dataset[0][1], values[1], split="|")[0], values[1]))
field = 3
for i in dataset[0][3:]:
if not np.issubdtype(dataframe.dtypes[field], np.number):
#print field
a.extend(buildOHE(one_hot(str(i), values[field], split="|")[0],values[field] ))
else:
a.append(i)
field+=1
newdataset.append(a)
for line in dataset[1:,:]:
#print line
case=line[0]
if case==caseID:
#print "case", case
#continues the current case
t = time.strptime(line[2], "%Y-%m-%d %H:%M:%S")
midnight = datetime.fromtimestamp(time.mktime(t)).replace(hour=0, minute=0, second=0, microsecond=0)
timesincemidnight = (datetime.fromtimestamp(time.mktime(t)) - midnight).total_seconds()
temptarget.append(datetime.fromtimestamp(time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S"))))
a=[(datetime.fromtimestamp(
time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))- starttime).total_seconds()]
a.append(( datetime.fromtimestamp(
time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))- lastevtime).total_seconds() )
a.append(timesincemidnight)
a.append(datetime.fromtimestamp(time.mktime(t)).weekday()+1)
lastevtime = datetime.fromtimestamp(
time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))
a.extend(buildOHE(one_hot(line[1], values[1], split="|")[0],values[1]) )
field=3
for i in line[3:]:
if not np.issubdtype(dataframe.dtypes[field], np.number):
#print "object", field
a.extend(buildOHE(one_hot(str(i), values[field], split="|")[0], values[field]))
else:
a.append(i)
field+=1
newdataset.append(a)
n+=1
finishtime=datetime.fromtimestamp(time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))
else:
caseID=case
for i in xrange(1,len(newdataset)): # +1 not adding last case. target is 0, not interesting. era 1
data.append(newdataset[:i])
#print newdataset[:i]
newdataset=[]
starttime = datetime.fromtimestamp(time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))
lastevtime = datetime.fromtimestamp(
time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))
t = time.strptime(line[2], "%Y-%m-%d %H:%M:%S")
midnight = datetime.fromtimestamp(time.mktime(t)).replace(hour=0, minute=0, second=0, microsecond=0)
timesincemidnight = (datetime.fromtimestamp(time.mktime(t)) - midnight).total_seconds()
a=[(datetime.fromtimestamp(
time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))- starttime).total_seconds() ]
a.append((datetime.fromtimestamp(
time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))-lastevtime).total_seconds() )
a.append(timesincemidnight)
a.append(datetime.fromtimestamp(time.mktime(t)).weekday()+1)
a.extend(buildOHE(one_hot(line[1], values[1], split="|")[0],values[1]) )
field=3
for i in line[3:]:
if not np.issubdtype(dataframe.dtypes[field], np.number):
a.extend(buildOHE(one_hot(str(i), values[field], split="|")[0], values[field]))
else:
a.append(i)
field+=1
newdataset.append(a)
for i in range(n): # era n
temptarget[-(i+1)]=(finishtime-temptarget[-(i+1)]).total_seconds()
temptarget.pop() #remove last element with zero target
temptarget.append(datetime.fromtimestamp(time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S"))))
finishtime=datetime.fromtimestamp(time.mktime(time.strptime(line[2], "%Y-%m-%d %H:%M:%S")))
n = 1
#last case
for i in xrange(1, len(newdataset) ): #+ 1 not adding last event, target is 0 in that case. era 1
data.append(newdataset[:i])
#print newdataset[:i]
for i in range(n): # era n. rimosso esempio con singolo evento
temptarget[-(i + 1)] = (finishtime - temptarget[-(i + 1)]).total_seconds()
#print temptarget[-(i + 1)]
temptarget.pop() # remove last element with zero target
#print temptarget
print "Generated dataset with n_samples:", len(temptarget)
assert(len(temptarget)== len(data))
#print temptarget
return data, temptarget
return generate_set(datasetTR), generate_set(datasetTS)