一、用列表+循环实现,并包装成函数
def pySum(n):
a = list(range(n))
b = list(range(0,5*n,5))
c = []
for i in range(len(a)):
c.append(a[i] ** 2 + b[i] ** 3)
return (c)
print(pySum(5))
结果如下:
二、用numpy实现,并包装成函数
import numpy
a = numpy.arange(5)
b = numpy.arange(0,20,4)
c = a+b
print(a,b,c)
三、对比两种方法实现的效率,给定一个较大的参数n,用运行函数前后的timedelta表示。
给定n=30,可以看出,以array为对象的numpy计算方式最快,而以numpy直接计算最慢,内置函数速度排第二。
def pySum(n):
a = list(range(n))
b = list(range(0,5*n,5))
c = []
for i in range(len(a)):
c.append(a[i] ** 2 + b[i] ** 3)
return (c)
print(pySum(30))
import numpy
def npSum(n):
a = numpy.arange(10)
b = numpy.arange(0,50,5)
c = a+b
return c
print(npSum(10))
from datetime import datetime
start = datetime.now()
pySum(100000)
delta = datetime.now()-start
print(delta)
from datetime import datetime
start = datetime.now()
npSum(100000)
delta = datetime.now()-start
print(delta)