合集-python
摘要：程序文件ex2_2.py import numpy as np a=[] with open('data2_2.txt') as f: for (i, s) in enumerate(f): a.append([s.count('a'), s.count('c'), s.count('g'),s.c
阅读全文
摘要：程序文件ex2_3.py L = ['abc', 12, 3.45, 'Python', 2.789] print(L) #输出完整列表 print(L[0]) #输出列表的第一个元素 L[0] = 'a' #修改列表的第一个元素 L[1:3] = ['b', 'Hello'] #修改列表的第二、三
阅读全文
摘要：程序文件ex2_4.py a=[[1,2,3],[4,5,6],[7,8,9]] d=[c for b in a for c in b] print(d)
阅读全文
摘要：程序文件ex2_5_1.py import os fn=[filename for filename in os.listdir('D:\Programs\Python\Python37') if filename.endswith(('.exe','.py'))] print(fn)
阅读全文
摘要：程序文件ex2_5_2.py from numpy.random import randint import numpy as np a=randint(10,20,16) #生成16个[10,20)上的随机整数 ma=max(a) ind1=[index for index,value in en
阅读全文
摘要：程序文件ex2_6.py T = ('abc', 12, 3.45, 'Python', 2.789) print(T) #输出完整元组 print(T[-1]) #输出元组的最后一个元素 print(T[1:3]) #输出元组的第二、三元素
阅读全文
摘要：程序文件ex2_7.py student = {'Tom', 'Jim', 'Mary', 'Tom', 'Jack', 'Rose'} print(student) a = set('abcdabc') print(a) #每次输出是不一样的，如输出：{'d', 'b', 'a', 'c'}
阅读全文
摘要：程序文件ex2_8.py dict1 ={'Alice': '123', 'Beth': '456', 'Cecil': 'abc'} print(dict1['Alice']) #输出123 dict1['new'] = 'Hello' #增加新的键值对 dict1['Alice'] = '123
阅读全文
摘要：程序文件ex2_10.py Dict={'age':18, 'score':[98,97], 'name':'Zhang', 'sex':'male'} for item in Dict: #遍历输出字典的“键” print(item) print(" " ) for item in Dict.it
阅读全文
摘要：程序文件ex2_11_1.py import string import random x=string.ascii_letters+string.digits y=''.join([random.choice(x) for i in range(1000)]) choice()用于从多个元素中随机
阅读全文
摘要：程序文件ex2_11_2.py import string, random, collections #依次加载三个模块 x=string.ascii_letters+string.digits y=''.join([random.choice(x) for i in range(1000)]) c
阅读全文
摘要：程序文件ex2_12_2.py def factorial(n): #定义阶乘函数 r = 1 while n > 1: r *= n n -= 1 return r def fib(n): #定义输出斐波那契数列函数 a, b = 1, 1 while a < n: print(a, end='
阅读全文
摘要：程序文件ex2_12_3.py from ex2_12_2 import factorial, fib print('%d!=%d'%(5,factorial(5))) fib(200)
阅读全文
摘要：程序文件ex2_14.py f=lambda x, y, z: xyz L=lambda x: [x2, x3, x**4] print(f(3,4,5)); print(L(2))
阅读全文
摘要：程序文件ex2_16.py from random import sample from numpy.random import randint a=sample(range(10),5) #在[0,9]区间上选择不重复的5个整数 b=randint(0,10,5) #在[0,9]区间上生成5个随机
阅读全文
摘要：程序文件ex2_18.py from ex2_12_2 import * print(factorial(6)) fib(300)
阅读全文
摘要：程序文件ex2_20.py x1="abcde" x2=list(enumerate(x1)) for ind,ch in enumerate(x1): print(ch)
阅读全文
摘要：程序文件ex2_22.py a = filter(lambda x: x>10,[1,11,2,45,7,6,13]) b = filter(lambda x: x.isalnum(),['abc', 'xy12', '***']) isalnum()是测试是否为字母或数字的方法 print(lis
阅读全文
摘要：程序文件ex2_24.py s1=[str(x)+str(y) for x,y in zip(['v']*4,range(1,5))] s2=list(zip('abcd',range(4))) print(s1); print(s2)
阅读全文
摘要：程序文件ex2_26.py import numpy as np a = np.ones(4, dtype=int) #输出[1, 1, 1, 1] b = np.ones((4,), dtype=int) #同a c= np.ones((4,1)) #输出4行1列的数组 d = np.zeros(
阅读全文
摘要：程序文件ex2_28.py import numpy as np a = np.arange(16).reshape(4,4) #生成4行4列的数组 b = np.floor(5np.random.random((2, 4))) c = np.ceil(6np.random.random((4, 2
阅读全文
摘要：程序文件ex2_30.py import numpy as np a = np.array([[0, 3, 4], [1, 6, 4]]) b = a.sum() #使用方法，求矩阵所有元素的和 c1 = sum(a) #使用内置函数，求矩阵逐列元素的和 c2 = np.sum(a, axis=0)
阅读全文
摘要：import numpy as np import math from scipy.optimize import minimize, Bounds def func(x): return sum(math.sqrt(x[i]) for i in range(100)) def con(x): re
阅读全文
摘要：把max放进约束条件,不妨假定小于等于10000 linprog from scipy.optimize import linprog c=[0,0,3,2] A=[[-1,-1,0,0],[0,0,-1,-1],[3,0,2,0],[0,3,0,2],[100,90,80,70]] b=[[-30
阅读全文
摘要：import cvxpy as cp import numpy as np import pandas as pd from scipy.optimize import minimize import sympy as sp sp.init_printing(use_unicode=True) im
阅读全文
摘要：import numpy as np from scipy.interpolate import interp1d, interp2d, UnivariateSpline, griddata import matplotlib.pyplot as plt t0 = np.linspace(700,
阅读全文
摘要：import numpy as np from scipy.interpolate import interp1d, interp2d, UnivariateSpline, griddata import matplotlib.pyplot as plt np.random.seed(114514)
阅读全文
摘要：import numpy as np import pandas as pd import sympy as sp sp.init_printing(use_latex=True) from scipy.integrate import odeint import matplotlib.pyplot
阅读全文
摘要：import numpy as np import pandas as pd import sympy as sp sp.init_printing(use_latex=True) from scipy.integrate import odeint import matplotlib.pyplot
阅读全文
摘要：edges = [ ("Pe", "T", 13), ("Pe", "N", 68), ("Pe", "M", 78), ("Pe", "L", 51), ("Pe", "Pa", 51), ("T", "N", 68), ("T", "M", 70), ("T", "L", 6
阅读全文
摘要：import heapq def prim(graph, start): num_nodes = len(graph) visited = [False] * num_nodes min_heap = [(0, start, -1)] mst_cost = 0 mst_edges = [] whil
阅读全文
摘要：initial_costs = [2.5, 2.6, 2.8, 3.1] salvage_values = [2.0, 1.6, 1.3, 1.1] maintenance_costs = [0.3, 0.8, 1.5, 2.0] dp = [[float('inf')] * 2 for _ in
阅读全文
浙公网安备 33010602011771号