updated the function's return types

PAMI/AssociationRules/basic/_ARWithLeverage.py

@@ -54,7 +54,7 @@
 
 
 from PAMI.AssociationRules.basic import abstract as _ab
-from typing import List, Dict, Tuple, Set, Union, Any, Generator
+#from typing import List, Dict, Tuple, Set, Union, Any, Generator
 from deprecated import deprecated
 
 
@@ -97,7 +97,7 @@ def _generation(self, prefix, suffix) -> None:
 
 
         if len(suffix) == 1:
-            conf = self._generateWithLeverage(prefix, suffix[0])
+            self._generateWithLeverage(prefix, suffix[0])
         for i in range(len(suffix)):
             suffix1 = suffix[:i] + suffix[i + 1:]
             prefix1 = prefix + ' ' + suffix[i]
@@ -140,7 +140,7 @@ def run(self) -> None:
             suffix = self._singleItems[:i] + self._singleItems[i + 1:]
             prefix = self._singleItems[i]
             for j in range(i + 1, len(self._singleItems)):
-                conf = self._generateWithLeverage(self._singleItems[i], self._singleItems[j])
+                self._generateWithLeverage(self._singleItems[i], self._singleItems[j])
             self._generation(prefix, suffix)
 
 
@@ -234,6 +234,7 @@ def __init__(self, iFile, minConf, sep) -> None:
         :type sep: str
         :return: None
         """
+        self._frequentPattern = None
         self._iFile = iFile
         self._minConf = minConf
         self._finalPatterns = {}

PAMI/extras/syntheticDataGenerator/GeoReferentialTemporalDatabase.py

@@ -18,7 +18,7 @@ class GeoReferentialTemporalDatabase:
             No of transactions
         noOfItems : int or float
             No of items
-        avgTransactionLength : str
+        avgTransactionLength : int
             The length of average transaction
         outputFile: str
             Name of the output file.
@@ -90,21 +90,21 @@ def performCoinFlip(self, probability: float) -> bool:
         result = np.random.choice([0, 1], p=[1 - probability, probability])
         return result
 
-    def tuning(self, array, sumRes) -> list:
+    def tuning(self, array, sumRes) -> np.ndarray:
         """
         Tune the array so that the sum of the values is equal to sumRes
 
         :param array: list of values
 
-        :type array: list
+        :type array: numpy.ndarray
 
         :param sumRes: the sum of the values in the array to be tuned
 
         :type sumRes: int
 
         :return: list of values with the tuned values and the sum of the values in the array to be tuned and sumRes is equal to sumRes
 
-        :rtype: list
+        :rtype: numpy.ndarray
         """
 
         while np.sum(array) != sumRes:
@@ -118,17 +118,17 @@ def tuning(self, array, sumRes) -> list:
                 array[minIndex] += 1
         return array
 
-    def generateArray(self, nums, avg, maxItems) -> list:
+    def generateArray(self, nums, avg, maxItems) -> np.ndarray:
         """
         Generate a random array of length n whose values average to m
 
         :param nums: number of values
 
-        :type nums: list
+        :type nums: int
 
         :param avg: average value
 
-        :type avg: float
+        :type avg: int
 
         :param maxItems: maximum value
 

PAMI/extras/syntheticDataGenerator/GeoReferentialTransactionalDatabase.py

@@ -103,21 +103,21 @@ def __init__(self, databaseSize, avgItemsPerTransaction, numItems, x1, y1, x2, y
         self._endTime = float()
         self._memoryUSS = float()
         self._memoryRSS = float()
-    def tuning(self, array, sumRes) -> list:
+    def tuning(self, array, sumRes) -> np.ndarray:
         """
         Tune the array so that the sum of the values is equal to sumRes
 
         :param array: list of values
 
-        :type array: list
+        :type array: numpy.ndarray
 
         :param sumRes: the sum of the values in the array to be tuned
 
         :type sumRes: int
 
         :return: list of values with the tuned values and the sum of the values in the array to be tuned and sumRes is equal to sumRes
 
-        :rtype: list
+        :rtype: numpy.ndarray
         """
 
         while np.sum(array) != sumRes:
@@ -131,25 +131,25 @@ def tuning(self, array, sumRes) -> list:
                 array[minIndex] += 1
         return array
 
-    def generateArray(self, nums, avg, maxItems) -> list:
+    def generateArray(self, nums, avg, maxItems) -> np.ndarray:
         """
         Generate a random array of length n whose values average to m
 
         :param nums: number of values
 
-        :type nums: list
+        :type nums: int
 
         :param avg: average value
 
-        :type avg: float
+        :type avg: int
 
         :param maxItems: maximum value
 
         :type maxItems: int
 
         :return: random array
 
-        :rtype: list
+        :rtype: numpy.ndarray
         """
 
         # generate n random values

PAMI/extras/syntheticDataGenerator/SequentialDatabase.py

@@ -94,7 +94,7 @@ def __init__(self, numSeq, avgItemsetPerSeq, avgItemsPerItemset, numItems, maxIt
         self.seqSep = seqSep
         self.db = []
 
-    def tuning(self, array, sumRes) -> list:
+    def tuning(self, array, sumRes) -> np.ndarray:
         """
         Tune the array so that the sum of the values is equal to sumRes
 
@@ -123,17 +123,17 @@ def tuning(self, array, sumRes) -> list:
                 array[randIndex] += 1
         return array
 
-    def generateArray(self, nums, avg, maxItems) -> list:
+    def generateArray(self, nums, avg, maxItems) -> np.ndarray:
         """
         Generate a random array of length nums whose values average to avg
 
         :param nums: number of values
 
-        :type nums: list
+        :type nums: int
 
         :param avg: average value
 
-        :type avg: float
+        :type avg: int
 
         :param maxItems: maximum value
 

PAMI/extras/syntheticDataGenerator/_TransactionalDatabase.py

@@ -107,7 +107,7 @@ def __init__(self, databaseSize, avgItemsPerTransaction, numItems,sep = "\t") ->
         self.sep = sep
         self.db = []
 
-    def _generateArray(self, nums, avg, maxItems) -> list:
+    def _generateArray(self, nums, avg, maxItems):
         """
         Generate a random array of length n whose values average to m
 

PAMI/extras/syntheticDataGenerator/createSyntheticGeoreferentialTransactions.py

@@ -61,7 +61,7 @@ def createGeoreferentialTransactionalDatabase(self, outputFile):
             writer.write("%s \n" % st)
 
 if __name__ == "__main__":
-    _ap = str()
+    #_ap = str()
     _ap = createSyntheticGeoreferentialTransaction(100000, 870, 10)
     _ap.createGeoreferentialTransactionalDatabase("T10_geo.txt")
 else:

PAMI/extras/syntheticDataGenerator/createSyntheticGeoreferentialUncertainTransaction.py

@@ -65,7 +65,7 @@ def createGeoreferentialUncertainTransactionalDatabase(self, outputFile: str) ->
             writer.write("%s \n" % st1)
 
 if __name__ == "__main__":
-    _ap = str()
+    #_ap = str()
     _ap = createSyntheticGeoreferentialUncertainTransaction(100000, 870, 10)
     _ap.createGeoreferentialUncertainTransactionalDatabase("T10_geo_un.txt")
 else:

PAMI/extras/syntheticDataGenerator/createSyntheticTemporal.py

@@ -51,7 +51,7 @@ def createTemporalDatabase(self, outputFile: str) -> None:
             count += 1
 
 if __name__ == "__main__":
-    _ap = str()
+    #_ap = str()
     _ap = createSyntheticTemporal(100000, 870, 10)
     _ap.createTemporalDatabase("temporal_T10.txt")
 else:

PAMI/extras/syntheticDataGenerator/createSyntheticTransactions.py

@@ -49,7 +49,7 @@ def createTransactionalDatabase(self, outputFile: str) -> None:
             writer.write("%s \n" % st)
 
 if __name__ == "__main__":
-    _ap = str()
+    #_ap = str()
     _ap = createSyntheticTransaction(100000, 870, 10)
     _ap.createTransactionalDatabase("T10.txt")
 else:

PAMI/extras/syntheticDataGenerator/createSyntheticUncertainTemporal.py

@@ -58,7 +58,7 @@ def createUncertainTemporalDatabase(self, outputFile: str) -> None:
 
 
 if __name__ == "__main__":
-    _ap = str()
+    #_ap = str()
     _ap = createSyntheticUncertainTemporal(50000, 870, 10)
     _ap.createUncertainTemporalDatabase("T10_uncertain_temp.txt")
 else:

PAMI/extras/syntheticDataGenerator/createSyntheticUncertainTransactions.py

@@ -56,7 +56,7 @@ def createUncertainTransactionalDatabase(self, outputFile: str) -> None:
 
 
 if __name__ == "__main__":
-    _ap = str()
+    #_ap = str()
     _ap = createSyntheticUncertainTransaction(100000, 870, 10)
     _ap.createUncertainTransactionalDatabase("T10_uncertain.txt")
 else:

PAMI/extras/syntheticDataGenerator/createSyntheticUtility.py

@@ -63,7 +63,7 @@ def createUtilityDatabase(self, outputFile: str) -> None:
             writer.write("%s \n" % st1)
 
 if __name__ == "__main__":
-    _ap = str()
+    #_ap = str()
     _ap = createSyntheticUtility(100000, 870, 100, 10)
     _ap.createUtilityDatabase("T10_util.txt")
 else:

PAMI/extras/syntheticDataGenerator/generateSpatioTemporal.py

@@ -101,8 +101,8 @@ class generateSpatioTemporal:
     def getPoint(self, x1, y1, x2, y2):
         return (np.random.randint(x1, x2), np.random.randint(y1, y2))
 
-    def __init__(self, numOfTransactions: int, avgLenOfTransactions: int, 
-                 numItems: int, outputFile: str, x1, y1, x2, y2, percentage: int=50,
+    def __init__(self, numOfTransactions: int, avgLenOfTransactions: float,
+                 numItems: int, outputFile: str, x1, y1, x2, y2, percentage: float=50.0,
                  sep: str='\t', typeOfFile: str="Database") -> None:
 
         """
@@ -197,21 +197,21 @@ def performCoinFlip(self, probability: float) -> bool:
         return result == 1
 
 
-    def tuning(self, array, sumRes) -> list:
+    def tuning(self, array, sumRes):
         """
         Tune the array so that the sum of the values is equal to sumRes
 
-        :param array: list of values
+        :param array: numpy.ndarray of values
 
-        :type array: list
+        :type array: numpy.ndarray
 
         :param sumRes: the sum of the values in the array to be tuned
 
         :type sumRes: int
 
         :return: list of values with the tuned values and the sum of the values in the array to be tuned and sumRes is equal to sumRes
 
-        :rtype: list
+        :rtype: numpy array
         """
 
         while np.sum(array) != sumRes:
@@ -227,17 +227,17 @@ def tuning(self, array, sumRes) -> list:
         return array
 
 
-    def generateArray(self, nums, avg, maxItems, sumRes) -> list:
+    def generateArray(self, nums, avg, maxItems, sumRes):
         """
         Generate a random array of length n whose values average to m
 
         :param nums: number of values
 
-        :type nums: list
+        :type nums: int
 
         :param avg: average value
 
-        :type avg: float
+        :type avg: int
 
         :param maxItems: maximum value
 
@@ -339,6 +339,6 @@ def save(self, sep, filename) -> None:
 
 
 
-    obj = generateSpatioTemporal(sys.argv[1], sys.argv[2], sys.argv[3], sys.argv[4], sys.argv[5], sys.argv[6], sys.argv[7], sys.argv[8])
+    obj = generateSpatioTemporal(int(sys.argv[1]), int(sys.argv[2]), int(sys.argv[3]), sys.argv[4], int(sys.argv[5]), int(sys.argv[6]), int(sys.argv[7]), int(sys.argv[8]))
     obj.createTemporalFile()
-    obj.getFileName(sys.argv[9])
+    obj.getFileName()

PAMI/extras/syntheticDataGenerator/generateSpatioTransactional.py

@@ -47,7 +47,7 @@ class generateSpatioTransactional:
     :Attributes:
     numLines: int  
         - number of lines
-    avgItemsPerLine: int 
+    avgItemsPerLine: int
         - average number of items per line
     numItems: int 
         - total number of items
@@ -101,21 +101,21 @@ def __init__(self, numLines, avgItemsPerLine, numItems, x1, y1, x2, y2) -> None:
                 point = self.getPoint(x1, y1, x2, y2)
             self.itemPoint[i] = point
 
-    def tuning(self, array, sumRes) -> list:
+    def tuning(self, array, sumRes):
         """
         Tune the array so that the sum of the values is equal to sumRes
 
-        :param array: list of values
+        :param array: numpy.ndarray of values of values
 
-        :type array: list
+        :type array: numpy.ndarray of values
 
         :param sumRes: the sum of the values in the array to be tuned
 
         :type sumRes: int
 
         :return: list of values with the tuned values and the sum of the values in the array to be tuned and sumRes is equal to sumRes
 
-        :rtype: list
+        :rtype: numpy array
         """
 
         while np.sum(array) != sumRes:
@@ -131,25 +131,25 @@ def tuning(self, array, sumRes) -> list:
         return array
 
 
-    def generateArray(self, nums, avg, maxItems) -> list:
+    def generateArray(self, nums, avg, maxItems):
         """
         Generate a random array of length n whose values average to m
 
         :param nums: number of values
 
-        :type nums: list
+        :type nums: int
 
         :param avg: average value
 
-        :type avg: float
+        :type avg: int
 
         :param maxItems: maximum value
 
         :type maxItems: int
 
         :return: random array
 
-        :rtype: list
+        :rtype: numpy array
         """
 
         # generate n random values
@@ -235,8 +235,8 @@ def getTransactions(self) -> pd.DataFrame:
     db.save('\t','2.txt')
     print(db.getTransactions())
 
-    obj = generateSpatioTransactional(sys.argv[1], sys.argv[2], sys.argv[3], sys.argv[4], sys.argv[5], sys.argv[6], sys.argv[7])
+    obj = generateSpatioTransactional(int(sys.argv[1]), int(sys.argv[2]), int(sys.argv[3]), int(sys.argv[4]), int(sys.argv[5]), int(sys.argv[6]), int(sys.argv[7]))
     obj.create()
-    obj.save(sys.argv[8])
+    #obj.save('\t',sys.argv[8])
     # print(obj.getTransactions())