摘要： 9.2 点击查看代码 import numpy as np from scipy.stats import shapiro data = [15.0, 15.8, 15.2, 15.1, 15.9, 14.7, 14.8, 15.5, 15.6, 15.3, 15.1, 15.3, 15.0, 15 阅读全文

摘要： 8.4 点击查看代码 import numpy as np import matplotlib.pyplot as plt from scipy.integrate import solve_ivp def system(t, state): x, y = state dxdt = -x*3 - y 阅读全文

摘要： 7.1 点击查看代码 import numpy as np import scipy.interpolate as spi import scipy.integrate as spi_integrate def g(x): return ((3*x**2 + 4*x + 6) * np.sin(x) 阅读全文

摘要： 6.5 点击查看代码 import numpy as np distances = np.array([ [0, 2, 7, np.inf, np.inf, np.inf], [2, 0, 4, 6, 8, np.inf], [7, 4, 0, 1, 3, np.inf], [np.inf, 6, 阅读全文

摘要： 4.3 点击查看代码 import matplotlib.pyplot as plt import numpy as np import cvxpy as cp x=cp.Variable(6,pos=True) obj=cp.Minimize(x[5]) a1=np.array([0.025, 0 阅读全文

摘要： 6.3 点击查看代码 import numpy as np import networkx as nx import pylab as plt L=[(1,2,20),(1,5,15),(2,3,20),(2,4,60),(2,5,25),(3,4,30),(3,5,18),(4,5,35),(4, 阅读全文

摘要： （a） 点击查看代码 import matplotlib.pyplot as plt # 创建一个无向图 G = nx.Graph() # 添加节点 G.add_nodes_from([1, 2, 3, 4, 5, 6]) # 添加边 edges = [(1, 2), (1, 3), (1, 4), 阅读全文

摘要： 5.7 点击查看代码 from scipy.optimize import minimize, NonlinearConstraint import numpy as np if __name__=="__main__": fun=lambda x:np.sum(50*x+0.2*x**2)+4*( 阅读全文

摘要： 2.2 点击查看代码 from scipy.special import gamma import pylab as plt import numpy as np plt.rc('text',usetex = True) x=np.linspace(-5,5,1000) plt.plot(x,gam 阅读全文

摘要： 点击查看代码 import numpy as np from scipy.optimize import minimize def objective(x): return -np.sum(np.sqrt(x) * np.arange(1, 101)) def constraint1(x): ret 阅读全文