一、求嵌入式列表中的最大最小值
import numpy as np sort=[[0.7275261282920837, 0.7496035099029541, 0.5761386156082153, 0.6948978900909424], [0.6625462770462036, 0.6829249262809753, 0.6067160367965698, 0.6217343211174011], [0.7260892987251282, 0.7354485988616943, 0.7215538024902344, 0.4761347770690918], [0.5674500465393066, 0.6440887451171875, 0.5788643956184387, 0.7181151509284973], [0.5206774473190308, 0.6888734698295593, 0.43109720945358276, 0.6093053817749023]] A=np.array(sort) print(A) print("最大数的索引是", np.argmax(A)) # 不加axix默认是全部 print("最小数的索引是", np.argmin(A)) print("每一列的最大值索引:", np.argmax(A, axis=0)) print("每一列的最小值索引:", np.argmin(A, axis=0)) print("每一行的最小值索引:", np.argmin(A, axis=1)) print("每一行的最大值索引:", np.argmax(A, axis=1)) #定义一个多维数组 #获得整个数组的最小值 print(A.min()) #获得每列最小值 print(A.min(0)) #获得每行最小值 print(A.min(-1))
运行结果
[[0.72752613 0.74960351 0.57613862 0.69489789] [0.66254628 0.68292493 0.60671604 0.62173432] [0.7260893 0.7354486 0.7215538 0.47613478] [0.56745005 0.64408875 0.5788644 0.71811515] [0.52067745 0.68887347 0.43109721 0.60930538]] 最大数的索引是 1 最小数的索引是 18 每一列的最大值索引: [0 0 2 3] 每一列的最小值索引: [4 3 4 2] 每一行的最小值索引: [2 2 3 0 2] 每一行的最大值索引: [1 1 1 3 1] 0.43109720945358276 [0.52067745 0.64408875 0.43109721 0.47613478] [0.57613862 0.60671604 0.47613478 0.56745005 0.43109721]
二、提取txt文件中的数据
def loaddata(filename): file = open(filename) frame = [] id = [] x = [] y = [] x2 = [] y2 = [] for line in file.readlines(): line = line.strip(',').split(',') frame.append(int(line[0])) id.append(str(line[1])) x.append(str(line[2])) y.append(str(line[3])) x2.append(str(line[4])) y2.append(str(line[5])) file.close() return frame, id, x, y, x2, y2 a,b,c,d,e,f=loaddata('result\1\result.txt') print(a) print(b) print(c) print(d)
运行结果