numpy學習筆記 - numpy數組的常見用法

# 純Python
def pythonSum(n):
    # 對列表迴圈計算
    a = [x for x in range(n)]
    b = [x for x in range(n)]
    c = []
    for i in range(len(a)):
        a[i] = i ** 2
        b[i] = i ** 3
        c.append(a[i] +b[i])
    return c

# numpy
def numpySum(n):
    # 直接對數組操作
    a = np.arange(n) ** 2
    b = np.arange(n) ** 3
    c = a + b
    return c

# 效率比較
size = 1000
# pythonSum()
start = datetime.now()  # 起始時間
c = pythonSum(size)
delta = datetime.now() - start  # pythonSum()的運行時間
print("The last two elements: ", c[-2:])    # 列印最後兩個元素，確認準確性
print("PythonSum elapsed time in microseconds: ", delta.microseconds)   # 以微秒為單位顯示運行時間

# pythonSum結果

The last two elements: [995007996, 998001000]
PythonSum elapsed time in microseconds: 999

# numpySum()
start = datetime.now()
c = numpySum(size)
delta = datetime.now() - start
print("The last two elements: ", c[-2:])
print("NumpySum elapsed time in microseconds: ", delta.microseconds)

# numpySum結果

The last two elements: [995007996 998001000]
NumpySum elapsed time in microseconds: 0

可以看出使用numpy數組的速度超快~