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import matplotlib import matplotlib.pyplot as plt # sphinx_gallery_thumbnail_number = 2 import pandas as pd import numpy as np from matplotlib.ticker import MultipleLocator, FormatStrFormatter d="EMD" ##i 可选项IQ、EMD、VMD f=8 ##j 可选项4、6、8 k=0.5 ##k 可选项1、0.5、0.1 datapath="./data/{}_test/sample{}/resnet{}/".format(d,k,f) datasave="./hunxiao_pdf/{}/sample{}/".format(d,k) data=pd.read_csv(datapath+"label.csv") pre=data['识别标签'] true=data['原始标签'] pre=np.array(pre) true=np.array(true) #生成12个计数变量a0~到a11 a=np.zeros((12,12),dtype=int) ##从csv文件中获得混淆矩阵数据 for i in range(26): start=int(i*13000) end=int((i+1)*13000) pre1=pre[start:end] true1=true[start:end] for j in range(len(pre1)): for z in range(12): if pre1[j]==z: a[i][z]=int(a[i][z])+1 print(a) a=np.array(a) plt.rc('font',family='Times New Roman') # 热度图,后面是指定的颜色块,可设置其他的不同颜色 font = {'family': 'Times New Roman', 'weight': 'normal', 'size': 8, } font1 = {'family': 'Times New Roman', 'weight': 'normal', 'size': 10, } ###设置每个子图大小 fig, ax = plt.subplots(figsize=(7,7)) # plt.figure(figsize=(5, 5)) ##画布颜色 # plt.imshow(a,cmap=plt.cm.Blues) im = ax.imshow(a,cmap=plt.cm.Blues,) ##设置坐标轴刻度 classes=['BPSK','QPSK','8PSK','OQPSK','2FSK','4FSK','8FSK','16QAM','32QAM','64QAM','4PAM','8PAM'] # We want to show all ticks... ###设置x,y轴长度 ax.set_xticks(np.arange(len(classes))) ax.set_yticks(np.arange(len(classes))) # ... and label them with the respective list entries ax.set_xticklabels(classes,fontdict=font) ax.set_yticklabels(classes,fontdict=font) plt.xlabel('Predicted label', font1) plt.ylabel('True lable', font1) # Rotate the tick labels and set their alignment. plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor") # Loop over data dimensions and create text annotations. for i in range(len(classes)): for j in range(len(classes)): text = ax.text(j, i, a[i, j], ha="center", va="center", color="brown",) # ax.set_title("data of local classes (in tons/year)") fig.tight_layout() plt.savefig(datasave+'resnet{}.pdf'.format(f), bbox_inches='tight') plt.show()
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