Construction of Selection and Evaluation Algorithm for High-Level Tennis Students in Colleges and Universities Based on Random Matrix Model

Table 1

Classification of evaluation indicators for selection.

Number	Classification of evaluation	Selection code text
Input	Indicators determined	Import numpy as np
Step 1	Primary secondary	Import matplotlib.pyplot as plt
Step 2	Basis was designed	Data = np.array([20, 50, 10, 15, 30, 55])
Step 3		Pie_labels = np.array([“A,” “B,” “C”])
Step 4	For the selection indicators	Norm = colors.Normalize()
Step 5	The algorithm step	Plt.contourf(X, Y, Z, 100, cmap = “bugn”)
Step 6	On the basis of	Cset = plt.contourf(X, Y, Z, cmap = “hot_r”)
Step 7	Matrix model	Alpha = 1,  = 0.0017,  = 0.0040
Step 8	The literature data	= 0.0017,  = 0.0040
Step 9	Combined with	X, Y = np.meshgrid (x, y)
Output	The random	Z = np.mat(an)