def InsertWorst(ValueT):
timeAr = np.zeros(ValueT, dtype=float)
for i in range(0, ValueT):
Ar1 = makeRevArray(i)
t = timeit.Timer(lambda: prg1.insertionSort(Ar1))
timeAr[i] = scipy.mean(t.repeat(repeat=3, number=1))
return timeAr
def InsertWorst(ValueT):
timeAr = np.zeros(ValueT, dtype = float)
for i in range(0, ValueT):
Ar1 = makeRevArray(i)
t = timeit.Timer(lambda: prg1.insertionSort(Ar1))
timeAr[i] = scipy.mean(t.repeat(repeat=3, number=1))
return timeAr
def getAverageInsertion(a):
avgArray = np.zeros(10, dtype=float)
for j in range(0, 10):
np.random.seed(0)
np.random.permutation(a)
t = timeit.Timer(lambda: insertionSort(a))
avgArray[j] = scipy.mean(t.repeat(repeat=3, number=1))
average = np.average(avgArray)
return average
def getAverageInsertion(a):
avgArray = np.zeros(10, dtype=float)
for j in range(0,10):
np.random.seed(0)
np.random.permutation(a)
t = timeit.Timer(lambda: insertionSort(a))
avgArray[j] = scipy.mean(t.repeat(repeat=3,number=1))
average = np.average(avgArray)
return average
