def convertContinuousToCategorical(self, attrName, splits):
data = []
currentSplit = [splits[0], 0] # split number, index
splitTypes = []
# CREATE A LIST OF SPLIT TYPES
for idx, split in enumerate(
splits): # for every split, save a splitKey
if idx == 0: # If index is zero
splitTypes.append("<=" +
str(split)) # add just less than or equal
else: # If last element
splitTypes.append(
str(splits[idx - 1]) + "< x <=" + str(split)) #
splitTypes.append(">" + str(splits[len(splits) - 1]))
# UPDATE ATTRIBUTES TO REFELCT CHANGES
for attr in self.attributes:
if attr[0] == attrName:
attr[1] = splitTypes
newBin = util.categoricalBin(
splitTypes) # create a new bin to store our values
splitKey = splitTypes[0]
for idx, contVar in enumerate(
self.continuousVariables[attrName].getValues(
)): # for every continuous variable we have
if contVar > currentSplit[0] and currentSplit[1] != len(splits) - 1:
currentSplit = [
splits[currentSplit[1] + 1], currentSplit[1] + 1
]
splitKey = splitTypes[currentSplit[1]]
elif contVar > currentSplit:
splitKey = splitTypes[len(splitTypes) - 1]
# UPDATE REVERSE LOOKUP
rlKey = attrName + " " + str(float(contVar))
if rlKey not in self.lookup:
continue
newrlKey = attrName + " " + splitKey
for userId in self.lookup[
rlKey]: # for every user that has that continuous variable value
self.data[userId][attrName] = splitKey
if newrlKey in self.lookup:
self.lookup[newrlKey].append(userId)
else:
self.lookup[newrlKey] = [userId]
newBin.add(splitKey,
self.data[userId][settings.CLASSIFIER_NAME])
self.lookup.pop(rlKey)
self.continuousVariables.pop(attrName)
self.categoricalVariables[attrName] = newBin
def convertContinuousToCategorical(self, attrName, splits):
data = []
currentSplit = [splits[0], 0] # split number, index
splitTypes = []
# CREATE A LIST OF SPLIT TYPES
for idx, split in enumerate(splits): # for every split, save a splitKey
if idx == 0: # If index is zero
splitTypes.append("<=" + str(split)) # add just less than or equal
else: # If last element
splitTypes.append(str(splits[idx - 1]) + "< x <=" + str(split)) #
splitTypes.append(">" + str(splits[len(splits) - 1]))
# UPDATE ATTRIBUTES TO REFELCT CHANGES
for attr in self.attributes:
if attr[0] == attrName:
attr[1] = splitTypes
newBin = util.categoricalBin(splitTypes) # create a new bin to store our values
splitKey = splitTypes[0]
for idx, contVar in enumerate(self.continuousVariables[attrName].getValues()): # for every continuous variable we have
if contVar > currentSplit[0] and currentSplit[1] != len(splits) - 1:
currentSplit = [splits[currentSplit[1] + 1], currentSplit[1] + 1]
splitKey = splitTypes[currentSplit[1]]
elif contVar > currentSplit:
splitKey = splitTypes[len(splitTypes) - 1]
# UPDATE REVERSE LOOKUP
rlKey = attrName + " " + str(float(contVar))
if rlKey not in self.lookup:
continue
newrlKey = attrName + " " + splitKey
for userId in self.lookup[rlKey]: # for every user that has that continuous variable value
self.data[userId][attrName] = splitKey
if newrlKey in self.lookup:
self.lookup[newrlKey].append(userId)
else:
self.lookup[newrlKey] = [userId]
newBin.add(splitKey, self.data[userId][settings.CLASSIFIER_NAME])
self.lookup.pop(rlKey)
self.continuousVariables.pop(attrName)
self.categoricalVariables[attrName] = newBin
def readArff(fileSrc):
# main variables to be returned
relation = "" # relation
attributes = [] # attribute list
rawData = [] # main data storage
reverseLookup = {} # store by value for reverse lookup
continuousVariables = {}
categoricalVariables = {}
dataFile = codecs.open(fileSrc, 'rb', 'utf-8') # specify utf-8 encoding
print "Reading file..."
lines = dataFile.readlines() # read all lines
if settings.PROGRESS_BAR == True:
util.updateProgress(0) # create a progress bar
# test every line and extract its relevant information
for idx, line in enumerate(lines): # test each line
if settings.PROGRESS_BAR == True:
util.updateProgress(float(idx) / float(len(lines)))
if line[0] == '%': # ignore comments
continue
elif line[0] == '@': # if is metadata
if '@relation' in line: # if relation
arrayLine = line.split(" ")
relation = arrayLine[1]
elif "@attribute" in line: # if attribute
arrayLine = line.split(" ")
attributes.append([arrayLine[1]])
if "real" not in arrayLine[2]: # if attribute is not real (is categorical)
attrs = re.search('\{(.*?)\}', line).group() # select text between brackets
attrs = re.sub('[\{\}]', "", attrs) # remove brackets
newAttrs = attrs.split(", ")
options = []
for attr in newAttrs:
options.append(attr)
attributes[len(attributes) - 1].append(options)
else: # if it is real
attributes[len(attributes) - 1].append('real')
elif line[0] == " ":
continue
else:
line = line.replace(" ", "")
line = line.replace("\n", "")
line = line.split(",")
newDataEntry = {} # create a new object to store our row data
for idx, value in enumerate(line): # for every column of data
attribute = attributes[idx]
if util.isNumber(value): # convert string to float if it's a number
value = float(value)
# Add value to our reverse lookup under the key "attributeName attributeValue"
rlKey = attribute[0] + " " + str(value) # create key for our reverseLookup data structure
if rlKey in reverseLookup:
reverseLookup[rlKey].append(len(rawData)) # append index of our current row (the length of data) for quick lookup later
else:
reverseLookup[rlKey] = [len(rawData)] # create a new arrayList to store our indices if one does not already exist
# fill our newData Entry
newDataEntry[attribute[0]] = value # store the value under its proper key
# add variables to our bins
if attribute[1] == 'real': # if the attribute is real, we place it in a continuous bin
if attribute[0] in continuousVariables:
continuousVariables[attribute[0]].add(value, line[len(line) - 1]) # add our value to our continuous bin
else:
continuousVariables[attribute[0]] = util.continuousBin(attribute[0]) # instantiate a continuous bin to hold our variable
continuousVariables[attribute[0]].add(value, line[len(line) - 1])
else: # if the attribute is categorical, we place it in a categorical bin
if attribute[0] in categoricalVariables:
categoricalVariables[attribute[0]].add(value, line[len(line) - 1])
else:
categoricalVariables[attribute[0]] = util.categoricalBin(attribute[1])
categoricalVariables[attribute[0]].add(value, line[len(line) - 1])
rawData.append(newDataEntry) # append data entry to all of our data
# END OF FOR LOOP
results = {}
results['data'] = rawData
results['attributes'] = attributes
results['relation'] = relation
results['lookup'] = reverseLookup
results['continuousVariables'] = continuousVariables
results['categoricalVariables'] = categoricalVariables
if settings.PROGRESS_BAR == True:
util.updateProgress(1)
print "\nFile read complete \n"
return results
def readArff(fileSrc):
# main variables to be returned
relation = "" # relation
attributes = [] # attribute list
rawData = [] # main data storage
reverseLookup = {} # store by value for reverse lookup
continuousVariables = {}
categoricalVariables = {}
dataFile = codecs.open(fileSrc, 'rb', 'utf-8') # specify utf-8 encoding
print "Reading file..."
lines = dataFile.readlines() # read all lines
if settings.PROGRESS_BAR == True:
util.updateProgress(0) # create a progress bar
# test every line and extract its relevant information
for idx, line in enumerate(lines): # test each line
if settings.PROGRESS_BAR == True:
util.updateProgress(float(idx) / float(len(lines)))
if line[0] == '%': # ignore comments
continue
elif line[0] == '@': # if is metadata
if '@relation' in line: # if relation
arrayLine = line.split(" ")
relation = arrayLine[1]
elif "@attribute" in line: # if attribute
arrayLine = line.split(" ")
attributes.append([arrayLine[1]])
if "real" not in arrayLine[
2]: # if attribute is not real (is categorical)
attrs = re.search(
'\{(.*?)\}',
line).group() # select text between brackets
attrs = re.sub('[\{\}]', "", attrs) # remove brackets
newAttrs = attrs.split(", ")
options = []
for attr in newAttrs:
options.append(attr)
attributes[len(attributes) - 1].append(options)
else: # if it is real
attributes[len(attributes) - 1].append('real')
elif line[0] == " ":
continue
else:
line = line.replace(" ", "")
line = line.replace("\n", "")
line = line.split(",")
newDataEntry = {} # create a new object to store our row data
for idx, value in enumerate(line): # for every column of data
attribute = attributes[idx]
if util.isNumber(
value): # convert string to float if it's a number
value = float(value)
# Add value to our reverse lookup under the key "attributeName attributeValue"
rlKey = attribute[0] + " " + str(
value) # create key for our reverseLookup data structure
if rlKey in reverseLookup:
reverseLookup[rlKey].append(
len(rawData)
) # append index of our current row (the length of data) for quick lookup later
else:
reverseLookup[rlKey] = [
len(rawData)
] # create a new arrayList to store our indices if one does not already exist
# fill our newData Entry
newDataEntry[attribute[
0]] = value # store the value under its proper key
# add variables to our bins
if attribute[
1] == 'real': # if the attribute is real, we place it in a continuous bin
if attribute[0] in continuousVariables:
continuousVariables[attribute[0]].add(
value,
line[len(line) -
1]) # add our value to our continuous bin
else:
continuousVariables[attribute[0]] = util.continuousBin(
attribute[0]
) # instantiate a continuous bin to hold our variable
continuousVariables[attribute[0]].add(
value, line[len(line) - 1])
else: # if the attribute is categorical, we place it in a categorical bin
if attribute[0] in categoricalVariables:
categoricalVariables[attribute[0]].add(
value, line[len(line) - 1])
else:
categoricalVariables[
attribute[0]] = util.categoricalBin(attribute[1])
categoricalVariables[attribute[0]].add(
value, line[len(line) - 1])
rawData.append(
newDataEntry) # append data entry to all of our data
# END OF FOR LOOP
results = {}
results['data'] = rawData
results['attributes'] = attributes
results['relation'] = relation
results['lookup'] = reverseLookup
results['continuousVariables'] = continuousVariables
results['categoricalVariables'] = categoricalVariables
if settings.PROGRESS_BAR == True:
util.updateProgress(1)
print "\nFile read complete \n"
return results
