摘要：
import numpy as np import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D 模拟高程数据（假设数据已经过某种方式插值或生成） 这里我们创建一个简单的40x50网格，并填充随机高程值 x = np 阅读全文
摘要：
import numpy as np import matplotlib.pyplot as plt 定义x的范围 x = np.linspace(-10, 10, 400) 创建一个2行3列的子图布局 fig, axs = plt.subplots(2, 3, figsize=(12, 8)) 遍 阅读全文
摘要：
import numpy as np import matplotlib.pyplot as plt 定义x的范围 x = np.linspace(-10, 10, 400) 创建一个图形和坐标轴 plt.figure(figsize=(10, 6)) ax = plt.gca() 循环绘制每条曲线 阅读全文
摘要：
import numpy as np import matplotlib.pyplot as plt from scipy.integrate import quad def fun(t, x): return np.exp(-t) * (t ** (x - 1)) x = np.linspace( 阅读全文
摘要：
import numpy as np import matplotlib.pyplot as plt 定义 x 的范围 x = np.linspace(-5, 5, 400) 计算三个函数的值 y_cosh = np.cosh(x) y_sinh = np.sinh(x) y_half_exp = 阅读全文
摘要：
import numpy as np import matplotlib.pyplot as plt from scipy.optimize import curve_fit, leastsq, least_squares from scipy.constants import e def g(x, 阅读全文
摘要：
import numpy as np import pandas as pd import matplotlib.pyplot as plt from scipy.interpolate import interp1d, PchipInterpolator, CubicSpline from sci 阅读全文
摘要：
import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import griddata def f(x, y): x2 = x2 return (x2 - 2*x) * np.exp(-x2 - y2 - x 阅读全文
摘要：
import numpy as np import scipy.interpolate as spi import scipy.integrate as spi_integrate def g(x): return ((3x**2 + 4x + 6) * np.sin(x)) / (x**2 + 8 阅读全文
摘要：
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, 0.015, 0.055 阅读全文