需求如下：
- 1、在一個頁面中顯示兩張圖片
- 2、進入頁面可以使用滑鼠拖動各自的圖片，相互不受影響
- 3、進入頁面后可以使用滑鼠滾輪放大或縮小圖片，相互不受影響，即滑鼠移動到圖片A上，可對圖片A進行放大或縮小，圖片B不受影響，反之亦然
- 4、拖動需求同3
實作代碼：
import matplotlib.pyplot as plt
from PIL import Image
import numpy as np
class Scale:
def __init__(self,fig,base_scale=1.5):
self.fig=fig
self.base_scale=base_scale
self.x0 = None
self.y0 = None
self.x1 = None
self.y1 = None
self.xpress = None
self.ypress = None
self.cur_xlim = None
self.cur_ylim = None
self.press = None
self.fig.canvas.mpl_connect('scroll_event', self.enter_axes)
self.fig.canvas.mpl_connect("button_press_event", self.enter_axes)
self.fig.canvas.mpl_connect('button_press_event',self.onPress)
self.fig.canvas.mpl_connect('button_release_event',self.onRelease)
self.fig.canvas.mpl_connect('motion_notify_event',self.onMotion)
def enter_axes(self,event):
# print(f"enter axes {event.inaxes}")
axtemp = event.inaxes
self.cur_xlim=axtemp.get_xlim()
self.cur_ylim=axtemp.get_ylim()
# print(f"x {self.cur_xlim} y {self.cur_ylim}")
xdata=https://www.cnblogs.com/surpassme/p/event.xdata
ydata=event.ydata
if event.button =="up":
scale_factor=1/self.base_scale
elif event.button == "down":
scale_factor=self.base_scale
else:
scale_factor=1
new_width = (self.cur_xlim[1] - self.cur_xlim[0]) * scale_factor
new_height = (self.cur_ylim[1] - self.cur_ylim[0]) * scale_factor
relx = (self.cur_xlim[1] - xdata) / (self.cur_xlim[1] - self.cur_xlim[0])
rely = (self.cur_ylim[1] - ydata) / (self.cur_ylim[1] - self.cur_ylim[0])
axtemp.set_xlim([xdata - new_width * (1 - relx), xdata + new_width * (relx)])
axtemp.set_ylim([ydata - new_height * (1 - rely), ydata + new_height * (rely)])
self.fig.canvas.draw_idle()
def onPress(self,event):
axtemp = event.inaxes
if event.inaxes != axtemp:
return
self.cur_xlim = axtemp.get_xlim()
self.cur_ylim = axtemp.get_ylim()
self.press = self.x0, self.y0, event.xdata, event.ydata
self.x0, self.y0, self.xpress, self.ypress = self.press
def onMotion(self,event):
if self.press is None:
return
if event.inaxes != event.inaxes:
return
dx = event.xdata - self.xpress
dy = event.ydata - self.ypress
self.cur_xlim -= dx
self.cur_ylim -= dy
event.inaxes.set_xlim(self.cur_xlim)
event.inaxes.set_ylim(self.cur_ylim)
def onRelease(self,event):
self.press = None
event.inaxes.figure.canvas.draw_idle()
class ViewImg:
def __init__(self,imgPath):
self.imgPath=imgPath
def viewImage(self):
try:
img1=Image.open(self.imgPath[0])
img2=Image.open(self.imgPath[1])
imgList=[]
for item in [img1,img2]:
if item == img1:
scale=2000/item.size[0]
print(f"img1:{item},{scale}")
elif item == img2:
scale=3000/item.size[0]
print(f"img2:{item},{scale}")
width=int(item.size[0]*scale)
height=int(item.size[1]*scale)
print(f"(width,height):{(width,height)}")
item=item.resize((width,height),Image.ANTIALIAS)
item=np.array(item)
imgList.append(item)
if len(imgList)==2:
img1,img2=imgList
else:
print(f"讀取圖片數量出錯，{len(imgList)}")
return
except Exception as ex:
print(f"view image error\n{ex}")
return
else:
# 設定視窗最大化前引數
plt.switch_backend("QT5Agg")
fig=plt.figure("染色體圖和細胞圖")
# 添加1行2列格子并添加第一個子格
ax1=fig.add_subplot(1,2,1)
# 僅顯示坐標軸，但不顯示刻度線
plt.xticks([])
plt.yticks([])
# 顯示圖片
plt.imshow(img1, aspect="auto")
plt.axis('on')
# 添加1行2列格子并添加第二個子格
ax2=fig.add_subplot(1, 2, 2)
# 添加自動布局
plt.tight_layout()
plt.xticks([])
plt.yticks([])
plt.imshow(img2, aspect="auto")
plt.axis('on')
# 調整四周和子圖之間的間距
plt.subplots_adjust(left=0.005,right=0.995,bottom=0.005,top=0.995,wspace=0.010,hspace=0.1)
# 設定最大化
plt.get_current_fig_manager().window.showMaximized()
ax1.set_title("dna")
ax2.set_title("cell")
scale=Scale(fig)
plt.show()
if __name__ == '__main__':
imgPath=[r"C:\Users\Surpass\Documents\PycharmProjects\a.jpg",r"C:\Users\Surpass\Documents\PycharmProjects\b.jpg" ]
viewImg=ViewImg(imgPath)
viewImg.viewImage()
參考網址：
- 1.https://matplotlib.org/users/event_handling.html
- 2.https://blog.csdn.net/dcyywin8/article/details/84101319
轉載請註明出處，本文鏈接：https://www.uj5u.com/houduan/150252.html
標籤：Python