11.16
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368e204a10
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@ -11,15 +11,15 @@
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# def 方法2(self, 参数列表):
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# pass
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class Cat:
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name = ''
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name = 'lili'
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def __init__(self):
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# self.name = 'Tom'
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self.name = 'Tom'
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print('init')
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def __str__(self):
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return(self.name)
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def drink(self):
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print('drink')
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cat = Cat()
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cat.name = 'Tom'
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# cat.name = 'Jack'
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print(f'我是小猫{cat},我的id是{id(cat)}',cat,cat.name)
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cat.drink()
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@ -1,6 +1,6 @@
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# 文件重命名
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import os
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os.rename('test.txt', 'test.py') #重命名
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os.rename('test.txt', 'Week5 Monte Carlo Methods.py') #重命名
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# 删除文件
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import os
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@ -8,7 +8,7 @@ os.remove('test.txt') #删除
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# 复制文件
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import shutil
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shutil.copyfile('test.txt', 'test.py')
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shutil.copyfile('test.txt', 'Week5 Monte Carlo Methods.py')
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# 遍历文件夹下的文件
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import os
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@ -0,0 +1,7 @@
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l = [1,2,3,4,5]
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it = iter(l)
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print(next(it))
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print(next(it))
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print(next(it))
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print(next(it))
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@ -67,3 +67,5 @@ for i,ele in enumerate(a):
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@ -2,7 +2,7 @@
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x = [[1,2,3], [4,5,6], [7,8,9]]
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y = [num for i in x for num in i]
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print(y)
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print(f"y = [num for i in x for num in i] :{y}")
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y = []
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for i in x:
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for num in i:
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@ -14,35 +14,12 @@ x = [-1,-4,6,7.5,-2.3,9,-11]
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y = [i for i in x if i>0]
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print(y)
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x = [(x, y) for x in range(3) for y in range(3)]
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print(x)
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x = [[x, y] for x in range(3) for y in range(3)]
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print("[(x, y) for x in range(3) for y in range(3)]: ",x)
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x = [(x, y) for x in [1, 2, 3] for y in [3, 1, 4] if x != y]
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print(x)
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# 列表综合练习 写一个循环，不断的问用户想买什么，用户选择一个商品编号，
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# 就把对应的商品添加到购物车里，最终用户输入q退出时，打印购物车里的商品列表
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l1 = [['a',23],['b',34],['c',33],['d',345]]
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l2 = []
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print("商品列表****************")
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for (index, i) in enumerate(l1):
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print("商品{}，价格为{}", index, i)
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while True:
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choise = input("请输入你选择的商品编号：")
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if choise.isdigit():
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if int(choise) in range(len(l1)) :
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print("你选择的是{}".format(choise))
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l2.append(l1[int(choise)])
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print(l2)
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else:
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print("你选的商品不在列表中")
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elif choise == 'q':
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break
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if len(l2)>0:
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print("你选的商品如下：")
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for index,i in enumerate(l2):
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print("商品编号{},商品名称{}，商品价格{}".format(index,i[0],i[1]))
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print("[(x, y) for x in [1, 2, 3] for y in [3, 1, 4] if x != y]: ",x)
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@ -0,0 +1,138 @@
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# In this notebook, you will simulate a system with of three nuclei AA , BB and CC where AA decays into BB and BB decays into CC . If exposed to a neutron flux nucleus CC can be activated into a nucleus AA .
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import numpy
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from matplotlib import pyplot as plt
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import random
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# Implement a function that tells whether a transition has occured,
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# based on the transition probability and a random number. Use the random number r from random.random()
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# and use the procedure described in the notes so that the checks can work in a reproducible way.
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def has_transitioned(p):
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r = random.random()
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return True if p>r else False
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random.seed(9867)
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assert [ has_transitioned(0.5) for i in range(10)] == [False, False, True, False, False, False, False, True, False, True]
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def evolveOne(currentState, rules):
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# YOUR CODE HERE
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for r in rules:
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if currentState == r[0]:
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return r[1] if has_transitioned(r[2]) else r[0]
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else:
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continue
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else:
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return currentState
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# these tests are worth 1 mark
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alwaysDecayRules = [
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('A', 'B', 1.0),
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('B', 'C', 1.0)
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]
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assert evolveOne('A', alwaysDecayRules) == 'B'
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assert evolveOne('B', alwaysDecayRules) == 'C'
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# these tests are worth 2 mark
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random.seed(112211)
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testRules = [
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('A', 'B', 0.33),
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('B', 'C', 0.75)
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]
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assert evolveOne('A', testRules) == 'A'
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assert evolveOne('A', testRules) == 'A'
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assert evolveOne('A', testRules) == 'A'
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assert evolveOne('A', testRules) == 'A'
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assert evolveOne('A', testRules) == 'B'
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assert evolveOne('B', testRules) == 'B'
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assert evolveOne('B', testRules) == 'C'
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assert evolveOne('B', testRules) == 'C'
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assert evolveOne('B', testRules) == 'C'
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assert evolveOne('B', testRules) == 'C'
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# with no rules there should be no change
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assert evolveOne('C', testRules) == 'C'
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# Now implement a function that takes a list of states and transition them according to the rules passed as argument.
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# This function should return a new vector of states, it should not modify the state passed as an argument!
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def evolveMany(states, rules):
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newState = []
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# YOUR CODE HERE
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for s in states:
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newState.append(evolveOne(s,rules))
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return newState
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# these tests are worth 1 mark
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random.seed(112287)
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testRules = [
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('A', 'B', 0.33),
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('B', 'C', 0.75)
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]
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initialTestArray = ['A','B','C']*5
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evolvedTest = evolveMany(initialTestArray, testRules)
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targetArray = ['B', 'C', 'C', 'A', 'C', 'C', 'A', 'B', 'C', 'A', 'C', 'C', 'B', 'C', 'C']
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assert evolvedTest == targetArray
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# checks the initial array is left unchanged
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assert initialTestArray == ['A','B','C']*5
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# Define a function that evolves a system that starts with initial amounts NA, NB and NC of AA ,
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# BB and CC nuclei and evolved it in n_timestep from time t=0t=0 to t=tmaxt=tmax .
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# The function should return three arrays, one for each atom type, of the number of nuclei
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# of that type at each time step. Each array should contain n_timestep+1 elements including the initial amount.
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def evolve_system(NA, NB, NC, rules, n_step):
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state = (['A'] * NA)+(['B'] * NB)+(['C'] * NC)
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A_count = numpy.empty(n_step + 1, dtype=int)
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B_count = numpy.empty(n_step + 1, dtype=int)
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C_count = numpy.empty(n_step + 1, dtype=int)
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# YOUR CODE HERE
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A_count[0] = NA
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B_count[0] = NB
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C_count[0] = NC
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for i in range(n_step):
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state = evolveMany(state, rules)
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A_count[i+1] = state.count('A')
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B_count[i+1] = state.count('B')
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C_count[i+1] = state.count('C')
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return A_count, B_count, C_count
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# these tests are worth 2 marks
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rules = [
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('A', 'B', 0.0033),
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('B', 'C', 0.0075),
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('C', 'A', 0.009)
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]
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r1, r2, r3 = evolve_system(0, 0, 250, rules, 17)
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assert len(r1) == 18
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assert len(r2) == 18
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assert len(r3) == 18
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# these tests are worth 2 marks
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testrules = [
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('A', 'B', 0.086),
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('B', 'C', 0.075),
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('C', 'A', 0.19)
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]
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random.seed(9485)
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r1, r2, r3 = evolve_system(200, 200, 200, testrules, 20)
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print(r1)
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print(r2)
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print(r3)
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assert (r1 == [200, 213, 233, 250, 258, 251, 266, 263, 259, 260, 265, 259, 256,
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255, 258, 256, 259, 253, 249, 247, 253]).all()
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assert (r2 == [200, 198, 201, 206, 205, 214, 214, 212, 216, 221, 225, 234, 236,
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238, 234, 235, 231, 245, 253, 256, 252]).all()
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assert (r3 == [200, 189, 166, 144, 137, 135, 120, 125, 125, 119, 110, 107, 108,
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107, 108, 109, 110, 102, 98, 97, 95]).all()
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@ -3,10 +3,6 @@ import numpy as np
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x = ['北京', '上海', '深圳', '广州']
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y = [60000, 58000, 50000, 52000]
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plt.plot(x, y)
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plt.show()
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plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签
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plt.rcParams['axes.unicode_minus']=False #用来正常显示负号
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@ -2,6 +2,10 @@
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import numpy as np
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nparr = np.array([i for i in range(10)])
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np.zeros(10)
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print(nparr,)
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a = np.zeros(10)
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f = np.zeros(10,dtype=float)
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n = np.full((3,5),44)
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r = np.random.randint(0,100,size=(3,5))
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r2 = np.random.random((3,5))
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x = np.linspace(0,100,50)
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print(nparr,a,f,n,r,r2,x)
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@ -17,7 +17,7 @@ import matplotlib.pyplot as plt
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# 从雅虎获得股票数据
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# pip install pandas_datareader
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# import data reader package
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# import data reader 1.14 package
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import pandas_datareader as pdr
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# read data from Yahoo! Finance for a specific
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for i in range(1,9):
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for j in range(1,i+1):
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print(f"{i}*{j} = {i*j} ", end = "")
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print("")
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@ -0,0 +1,25 @@
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# 随机数的处理
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# 综合练习---猜数字
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# 计算机要求用户输入数值范围的最小值和最大值。
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# 计算机随后“思考”出在这个范围之内的一个随机数，
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# 并且重复地要求用户猜测这个数，直到用户猜对了。
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# 在用户每次进行猜测之后，计算机都会给出一个提示，
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# 并且会在这个过程的最后显示出总的猜测次数。这
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# 个程序包含了几种类型的我们学过的 Python 语句，例如，输入语句、输出语句、赋值语句、循环和条件语句
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import random
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smaller = int(input("Enter the smaller number: "))
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larger = int(input("Enter the larger number: "))
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myNumber = random.randint(smaller, larger)
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count = 0
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while True:
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count += 1
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userNumber = int(input("Enter your guess: "))
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if userNumber < myNumber:
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print("Too small")
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elif userNumber > myNumber:
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print("Too large")
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else:
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print("You've got it in", count, "tries!")
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break
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@ -44,7 +44,7 @@ def LassoRegression(degree, alpha):
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("std_scaler", StandardScaler()),
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("lasso_reg", Lasso(alpha=alpha))
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])
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lasso1_reg = LassoRegression(20, 0.01)
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lasso1_reg = LassoRegression(20, 0.1)
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lasso1_reg.fit(X_train, y_train)
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y1_predict = lasso1_reg.predict(X_test)
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mean_squared_error(y_test, y1_predict)
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