matplot-散点图

"""
散点图

"""
import matplotlib.pyplot as plt
import numpy as np
import scipy.io as sio
from matplotlib.font_manager import FontProperties
font = FontProperties(fname=r"C:\\WINDOWS\\Fonts\\msyhbd.ttf")

for i in range(1,15):#大循环1-14个电极，先绘制前七个电极，后绘制后七个电极
# 前七个电极的common method and improve method
if i<=7:
fig = plt.figure(1, figsize=(7, 9.84))
fig.subplots_adjust(left=0.05, bottom=0.055, right=0.98, top=0.975, wspace=0.13, hspace=0.09)

#the common method
path = './python/Common_method'
data_common=sio.loadmat(path+'/mean'+str(i)+'.mat')
mean_hon=data_common['mean_hon'].T
mean_hon_ave=data_common['mean_hon_ave'].T
mean_lying=data_common['mean_lying'].T
mean_lying_ave=data_common['mean_lying_ave'].T

x_num=np.arange(1,16,1)
ax1=fig.add_subplot(7,2,2*i-1)
ax1.scatter(x_num,mean_hon,color="#DAA520", s=35, marker='H')#DAA520 FF0000
if i==1:
ax1.set_yticks([0.4,0.6,0.8])
ax1.set_ylim(0.1, 0.95)
elif i in[2,3]:
ax1.set_ylim(0.1, 0.95)
ax1.set_yticks([0.2,0.4,0.6,0.8])
else:
ax1.set_ylim(0.0, 0.7)
ax1.set_yticks([0.2,0.4,0.6])
#判断最大值与最小值的范围
# ax1.set_ylim(mean_min,mean_max)
ax1.scatter(x_num,mean_lying,color="#FF0000", s=35, marker='H')
ax1.axhline(y=mean_hon_ave, xmin=0, xmax=15, linewidth=1.5, color='#DAA520')
ax1.axhline(y=mean_lying_ave, xmin=0, xmax=15, linewidth=1.5, color='#FF0000')
if i==7:
plt.text(5, -0.2, 'Subject number', fontproperties=font,fontsize=10)
#plt.xlabel('Subject number',fontproperties=font,)
plt.xticks([0,2,4,6,8,10,12,14,16])
else:
plt.xticks([])
if i==1:
plt.title('$Mean_{WE}^{P3}$',fontproperties=font,fontsize=13)

#Improve method
path = './python/Improve_method'
data_common = sio.loadmat(path + '/mean' + str(i) + '.mat')
mean_hon = data_common['mean_hon'].T
mean_hon_ave=data_common['mean_hon_ave'].T
mean_lying = data_common['mean_lying'].T
mean_lying_ave=data_common['mean_lying_ave'].T
x_num = np.arange(1, 16, 1)
ax2 = fig.add_subplot(7, 2, 2 * i )
ax2.scatter(x_num, mean_hon, color="#DAA520", s=35 ,marker='H')
ax2.scatter(x_num, mean_lying, color="#FF0000", s=35, marker='H')
ax2.axhline(y=mean_hon_ave, xmin=0, xmax=15, linewidth=1.5, color='#DAA520')
ax2.axhline(y=mean_lying_ave, xmin=0, xmax=15, linewidth=1.5, color='#FF0000')
if i==7:
plt.text(5, -0.23, 'Subject number', fontproperties=font,fontsize=10)
#plt.xlabel('Subject number',fontproperties=font,fontsize=10)
plt.xticks([0,2,4,6,8,10,12,14,16])
legend_char = ["group mean of innocent", "group mean of guilty", "mean of one innocent","mean of one guilty"]
plt.legend(legend_char, loc=(0.0, 0.0), ncol=4, frameon=False, title="", bbox_to_anchor=(-1.21, -0.47),
fontsize=7, labelspacing=0.0, handlelength=4)
else:
plt.xticks([])
if i in[1,2,3]:
ax2.set_yticks([0.2,0.4,0.6,0.8,1.0])
ax2.set_ylim(0.1,0.95)
else:
ax2.set_ylim(0.0,0.7)
ax2.set_yticks([0.2,0.4,0.6,0.8])
if i==1:
plt.title('$Impv_{WE}^{P3}$',fontproperties=font,fontsize=13)
# plt.savefig(".\png_figure\electrodes_fourteen_01" + '.png',dpi=600)

# 后七个电极的common method and improve method
if i>7:
fig = plt.figure(2, figsize=(7, 9.8))
fig.subplots_adjust(left=0.05, bottom=0.055, right=0.98, top=0.975, wspace=0.13, hspace=0.09)

#the common method
path = './python/Common_method'
data_common=sio.loadmat(path+'/mean'+str(i)+'.mat')
mean_hon=data_common['mean_hon'].T
mean_hon_ave=data_common['mean_hon_ave'].T
mean_lying=data_common['mean_lying'].T
mean_lying_ave=data_common['mean_lying_ave'].T

x_num=np.arange(1,16,1)
ax1=fig.add_subplot(7,2,2*(i-7)-1)
ax1.scatter(x_num,mean_hon,color="#DAA520", s=35, marker='H')#,alpha=0.6
#设定y轴的范围
if i in [8,9,10,11,12]:
ax1.set_yticks([0.2,0.4,0.6])
ax1.set_ylim(0.0, 0.7)
else:
ax1.set_ylim(0.2, 0.95)
ax1.set_yticks([0.2,0.4,0.6,0.8])
ax1.scatter(x_num,mean_lying,color="#FF0000", s=35, marker='H')#,alpha=0.6
ax1.axhline(y=mean_hon_ave, xmin=0, xmax=15, linewidth=1.5, color='#DAA520')
ax1.axhline(y=mean_lying_ave, xmin=0, xmax=15, linewidth=1.5, color='#FF0000')
if i==14:
plt.text(5, -0.02, 'Subject number', fontproperties=font, fontsize=10)
#plt.xlabel('Subject number',fontproperties=font,fontsize=10)
plt.xticks([0,2,4,6,8,10,12,14,16])
else:
plt.xticks([])
if i==8:
plt.title('$Mean_{WE}^{P3}$',fontproperties=font,fontsize=13)

#Improve method
path = './python/Improve_method'
data_common = sio.loadmat(path + '/mean' + str(i) + '.mat')
mean_hon = data_common['mean_hon'].T
mean_hon_ave=data_common['mean_hon_ave'].T
mean_lying = data_common['mean_lying'].T
mean_lying_ave=data_common['mean_lying_ave'].T
x_num = np.arange(1, 16, 1)
ax2 = fig.add_subplot(7, 2, 2 * (i-7) )
ax2.scatter(x_num, mean_hon, color="#DAA520", s=35 ,marker='H')
ax2.scatter(x_num, mean_lying, color="#FF0000", s=35, marker='H')
ax2.axhline(y=mean_hon_ave, xmin=0, xmax=15, linewidth=1.5, color='#DAA520')
ax2.axhline(y=mean_lying_ave, xmin=0, xmax=15, linewidth=1.5, color='#FF0000')
if i==14:
plt.text(5, -0.02, 'Subject number', fontproperties=font,fontsize=10)
#plt.xlabel('Subject number',fontproperties=font,fontsize=10)
plt.xticks([0,2,4,6,8,10,12,14,16])
legend_char = ["group mean of innocent", "group mean of guilty", "mean of one innocent",
"mean of one guilty"]
plt.legend(legend_char, loc=(0.0, 0.0), ncol=4, frameon=False, title="", bbox_to_anchor=(-1.21, -0.47),
fontsize=7, labelspacing=0.0, handlelength=4)
else:
plt.xticks([])
#设定y轴的范围
if i in [8,9,10,11,12]:
ax2.set_yticks([0.2,0.4,0.6])
ax2.set_ylim(0.0, 0.7)
else:
ax2.set_ylim(0.2, 0.95)
ax2.set_yticks([0.2,0.4,0.6,0.8])
if i==8:
plt.title('$Impv_{WE}^{P3}$',fontproperties=font,fontsize=13)
# plt.savefig(".\png_figure\electrodes_fourteen_02" + '.png',dpi=600)

plt.show()

# print(data_common.shape())