def __init__(self, transaction_list, row_size):
fs.FunctionsSuper.__init__(self)
self.__t_size = len(transaction_list) # all transaction size
self.__f_size = self.sumValue(
transaction_list) # transaction size which have flag = 1 (n1)
self.__pvalTable = pvalTable.PvalTable(row_size) # P-value table
self.__occrTable = pvalTable.PvalTable(
row_size) # occurence table for calculate P-value
self.calTime = 0 # Total number of calculate P-value
if self.__f_size == 0:
sys.stdout.write("Error: There is no up-regulate gene.\n")
sys.exit()
# Check the transaction value.
# If the value is not 1 or 0, raise error.
# Because fisher's exact test does not handle numerical value.
for t in transaction_list:
if not (t.value == 1.0 or t.value == 0.0):
sys.stderr.write("Error: \"" + t.name + "\" value is " +
str(t.value) + ".\n")
sys.stderr.write(
" But value is 1 or 0 if you test by fisher's exact test.\n"
)
sys.exit()
# check the support size.
# If support size larger than half of all data size, raise error.
# Because this version does not treat x > (n1+n0)/2.
"""
def __init__(self, transaction_list, row_size, alternative):
fs.FunctionsSuper.__init__(self)
self.__t_size = len(transaction_list) # all transaction size
self.__f_size = self.sumValue(
transaction_list) # transaction size which have flag = 1 (n1)
self.alternative = alternative # alternative hypothesis. greater or less -> 1, two.sided -> 0.
self.__pvalTable = pvalTable.PvalTable(row_size) # P-value table
self.__chiTable = pvalTable.PvalTable(row_size) # P-value table
if self.__f_size == 0:
sys.stdout.write("Error: There is no up-regulate gene.\n")
sys.exit()
# Check the transaction value.
# If the value is not 1 or 0, raise error.
# Because fisher's exact test does not handle numerical value.
for t in transaction_list:
if not (t.value == 1.0 or t.value == 0.0):
sys.stderr.write("Error: \"" + t.name + "\" value is " +
str(t.value) + ".\n")
sys.stderr.write(
" But value is 1 or 0 if you test by fisher's exact test.\n"
)
sys.exit()