Matplotlib drawing retouching (how to form high-quality drawings, such as how to set fonts, etc.)

Preface

Originally , If you just draw pictures by yourself and steal them by yourself , Generally, there is no such demand , Just default .

However , If you want to print and publish this picture , Or put it in the paper , Or put it in PPT Show in . You'll find that , The default graph is not very good . For example, in the paper , By default , The font inside will be particularly blurred .

import matplotlib.pyplot  as plt

The resolution of the

Add the following sentence at the beginning , It can make your picture not blurred .

plt.figure(dpi=300)

style

The style includes many conveniences , font size , Font format, etc .

1. Let's start with a global change , That is to say, add , Then it is globally valid , Very convenient .

plt.rcParams["font.weight"] = "bold"
plt.rcParams["axes.labelweight"] = "bold"

2. Then change it locally .

#  Modify the title and x,y Axis font and size 
plt.title("$MFCC_0$ Parameter median filter ", fontsize=15,fontweight='bold')
plt.xlabel(" Time /s", fontsize=15,fontweight='bold')
plt.ylabel(" The number ", fontsize=15,fontweight='bold')

#  Modify the axis font and size 
plt.yticks(fontproperties='Times New Roman', size=15,weight='bold')# Set size and bold 
plt.xticks(fontproperties='Times New Roman', size=15)


#  Set title 
plt.rcParams['font.sans-serif'] = ['KaiTi']  #  Used to display Chinese labels normally , If you want to use the New Roman font , Change to  Times New Roman
plt.rcParams['axes.unicode_minus'] = False  #  Used to display negative sign normally 
plt.tight_layout()  #  Solve the overlapping of upper and lower titles when drawing 

# Draw line 
plt.vlines(starts2time, min(Mfcc1)-10, max(Mfcc1)+10, colors="black", linestyles="solid",lw=2)
plt.vlines(ends2time, min(Mfcc1)-10, max(Mfcc1)+10, colors="black", linestyles="dashed",lw=2.5)

# Add legend 
plt.legend(['train acc','train loss'])# Add legend 
plt.legend(['train acc','train loss'],fontsize=12)# And set the size 



# Cancel the axis scale 
plt.xticks([])  #  Go to x Coordinate scale 
plt.yticks([])  #  Go to y Coordinate scale 
plt.axis('off')  #  Go to the axis 


# Cancel savefig White border when saving pictures 
plt.savefig(pic_name,bbox_inches='tight',pad_inches=0.0)

# Cancel the border of each 
ax1 = plt.subplot(2, 3, 1)
ax1.spines['right'].set_visible(False)	# On the right 
ax1.spines['top'].set_visible(False)	# above 
ax1.spines['left'].set_visible(False)	# On the left 
ax1.spines['bottom'].set_visible(False)	# Underside 

Reference resources

1.https://blog.csdn.net/weixin_38468077/article/details/117734027?utm_medium=distribute.pc_aggpage_search_result.none-task-blog-2_{aggregatepage}first_rank_ecpm_v1~rank_v31_ecpm-1-117734027-null-null.pc_agg_new_rank&utm_term=plt%E5%AD%97%E4%BD%93%E5%8A%A0%E7%B2%97&spm=1000.2123.3001.4430