How does Matplotlib and PIL image integrate and save multiple pictures into one picture

Catalog

1.  Law 1 ： Generate multi row and multi column graph

2.   Law two ： Generate a single line / Single column diagram

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        stay This article How to generate multiple graphs is described in , But many times, we need to comprehensively compare and display the pictures , Therefore, it needs to be merged in one picture .

        Here is 2 Methods ： Method 1 usually shows the idea of multiple rows and columns , Reference resources writing 1; Method 2 can be used to send a single line / Single column long graph , Reference resources writing 2.

1.  Law 1 ： Generate multi row and multi column graph

import os
import inspect
import pandas as pd
import numpy as np
from datetime import datetime
from PIL import Image
import glob, os
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['axes.unicode_minus']=False

prefix = 'flow'
# * matching 1 individual or Multiple characters ,files It can display all file names （ Tabular form ）
files=glob.glob('fig_lots/flow_*')
num=len(files)
img_np = []
# sz Represents the pixel of the picture 
sz = (2000, 1400)
for i in range(0, num):
    file = prefix+'_'+str(i+1)+'.png'
    #  Traverse and open these pictures , and resize by sz
    im = Image.open('fig_lots/'+file)
    im = im.resize(sz,Image.ANTIALIAS)
    #  Turn the picture into array
    im_array = np.atleast_2d(im)
    img_np.append(im_array)
#  The length of the picture 、 wide 、 The channel number 
print(im_array.shape[0], im_array.shape[1], im_array.shape[2])

#  Canvas size figsize according to sz and rows cols Jointly determine , That is, the canvas is horizontal ： Canvas portrait  = sz Length *cols ：sz The width of *rows
fig = plt.figure(figsize = (20, 39))
rows = 11
cols = 4
for i in range(1, rows*cols + 1):
    img_array = img_np[i-1]
    #  Subgraph location 
    ax = fig.add_subplot(rows, cols, i)
    plt.axis('off') #  Remove the axis of each subgraph 
    plt.imshow(img_array)

plt.subplots_adjust(wspace = 0, hspace = 0) #  Modify the interval between subgraphs 
plt.savefig('flowrc.png', dpi=400)

2.   Law two ： Generate a single line / Single column diagram

import numpy as np
from PIL import Image
import glob, os

#  Use only PIL Library by converting pictures to array Format , Merge export . Unable to adjust the size and spacing of the picture for the time being 、 Only one way 、 Single column Export .
if __name__=='__main__':
    # * matching 1 individual or Multiple characters ,files It can display all file names （ Tabular form ）
    files=glob.glob('fig_lots/flow_*')
    num=len(files)
    
    filename_lens=[len(x) for x in files] #length of the files
    min_len=min(filename_lens) #minimal length of filenames
    max_len=max(filename_lens) #maximal length of filenames
    if min_len==max_len:#the last number of each filename has the same length
        files=sorted(files) #sort the files in ascending order
    else:#maybe the filenames are:x_0.png ... x_10.png ... x_100.png
        index=[0 for x in range(num)]
        for i in range(num):
            filename=files[i]
            start=filename.rfind('_')+1
            end=filename.rfind('.')
            file_no=int(filename[start:end])
            index[i]=file_no
        index=sorted(index)
        files=[prefix+'_'+str(x)+'.png' for x in index]
        
    print(files[0], files)
    # Image.open Picture attribute 
    baseimg=Image.open('fig_lots/'+files[0])
    # .size Display size （2000,1400）
    sz=baseimg.size
    # 0-255 Of the displayed picture 2 Dimension group 
    basemat=np.atleast_2d(baseimg)
    #  From 2 The picture begins , Merge with the previous figure 
    for i in range(1,num):
        file=files[i]
        im=Image.open('fig_lots/'+file)
        im=im.resize(sz,Image.ANTIALIAS)
        #  The image is converted into an array 
        mat=np.atleast_2d(im)
        basemat=np.append(basemat,mat,axis=0)
    #  The image is converted back from the array 
    final_img=Image.fromarray(basemat)
    print(final_img)
    final_img.save('merged.png')

        Generating multiple graphs is “ discharge ”, Aggregated into a graph is “ closed ”,“ discharge ” Yes “ From thin to thick ” The feeling of ,“ closed ” Yes “ From thick to thin ” The feeling of .

        See a bunch of beautiful pictures , Happy ~~