2025年1月3日
第九章
摘要： 9.3 点击查看代码 import matplotlib.pyplot as plt data = [ [4.13, 3.86, 4.00, 3.88, 4.02, 4.02, 4.00], [4.07, 3.85, 4.02, 3.88, 3.95, 3.86, 4.02], [4.04, 4.0 阅读全文
posted @ 2025-01-03 20:38 2023310143015 阅读(18) 评论(0) 推荐(0)
第八章
摘要： 8.4代码 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 - 阅读全文
posted @ 2025-01-03 20:23 2023310143015 阅读(27) 评论(0) 推荐(0)
7.10
摘要： 代码 点击查看代码 import numpy as np import pandas as pd import matplotlib.pyplot as plt from scipy.interpolate import interp1d, PchipInterpolator, CubicSplin 阅读全文
posted @ 2025-01-03 20:17 2023310143015 阅读(12) 评论(0) 推荐(0)
7.7
摘要： 代码 点击查看代码 import numpy as np from scipy.optimize import curve_fit, least_squares from scipy.linalg import lstsq import matplotlib.pyplot as plt def g( 阅读全文
posted @ 2025-01-03 19:26 2023310143015 阅读(11) 评论(0) 推荐(0)
7.4
摘要： 代码 点击查看代码 import numpy as np from scipy.interpolate import griddata import matplotlib.pyplot as plt # 定义函数 def f(x, y): return (x ** 2 - 2 * x) * np.e 阅读全文
posted @ 2025-01-03 19:24 2023310143015 阅读(4) 评论(0) 推荐(0)
7.3
摘要： 代码 点击查看代码 import numpy as np from scipy.interpolate import interp1d, CubicSpline import matplotlib.pyplot as plt # 给定数据 T = np.array([700, 720, 740, 7 阅读全文
posted @ 2025-01-03 19:23 2023310143015 阅读(9) 评论(0) 推荐(0)
2024年10月28日
6.5
摘要： 代码 点击查看代码 import numpy as np import networkx as nx import pandas as pd import pylab as plt n=6 node=['v'+str(i) for i in range(1,n+1)] A=np.zeros((n,n 阅读全文
posted @ 2024-10-28 13:05 2023310143015 阅读(10) 评论(0) 推荐(0)
6.4
摘要： *代码 点击查看代码 import numpy as np import networkx as nx a=np.zeros((5,5)) a[0,1:]=[0.8,2,3.8,6] a[1,2:]=[0.9,2.1,3.9] a[2,3:]=[1.1,2.3]; a[3,4]=1.4 G=nx.D 阅读全文
posted @ 2024-10-28 13:04 2023310143015 阅读(10) 评论(0) 推荐(0)
6.3
摘要： 代码 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, 5, 25), (2, 3, 20), (2, 4, 60), (3, 5, 18), (3 阅读全文
posted @ 2024-10-28 13:03 2023310143015 阅读(14) 评论(0) 推荐(0)
6.1（3）
摘要： 点击查看代码 import networkx as nx import matplotlib.pyplot as plt G=nx.DiGraph() G.add_nodes_from([1,2,3,4,5,6]) edges_with_weights=[(1,3,3),(2,1,7),(2,3,1 阅读全文
posted @ 2024-10-28 13:02 2023310143015 阅读(11) 评论(0) 推荐(0)