lr580

import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import ConvexHull

# 设置中文字体（确保系统中有支持中文的字体，如SimHei）
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用于正常显示中文
plt.rcParams['axes.unicode_minus'] = False    # 用于正常显示负号

# 生成随机点集
# np.random.seed(42)

lr580

# paper Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

import numpy as np
import matplotlib.pyplot as plt

# 定义逆 sigmoid 函数
def inverse_sigmoid(i, tau):
    return tau / (tau + np.exp(i / tau))

# 设置参数

lr580

import sympy as sp

# 定义矩阵 A
A = sp.Matrix([
    [1, 0, 1],
    [0, 1, 1],
    [0, 0, 0]
])

# 定义 U, Sigma, V

lr580

import sympy as sp
A = sp.Matrix([
    [2,0,5,6, 1,0,0,0],
    [1,3,3,6, 0,1,0,0],
    [-1,1,2,1, 0,0,1,0],
    [1,0,1,3, 0,0,0,1]
])
def f(r1, r2, k): #r1+k*r2
    A[r1 - 1, :] = A[r1 - 1, :] + k * A[r2 - 1, :]
def g(r1, k): #r1*k

lr580

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