需求如下:
- 1、在一个页面中显示两张图片
- 2、进入页面可以使用鼠标拖动各自的图片,相互不受影响
- 3、进入页面后可以使用鼠标滚轮放大或缩小图片,相互不受影响,即鼠标移动到图片a上,可对图片a进行放大或缩小,图片b不受影响,反之亦然
- 4、拖动需求同3
实现代码:
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=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"读取图片数量出错,{len(imglist)}")
return
except exception as ex:
print(f"view image error\n{ex}")
return
else:
# 设置窗口最大化前参数
plt.switch_backend("qt5agg")
fig=plt.figure("染色体图和细胞图")
# 添加1行2列格子并添加第一个子格
ax1=fig.add_subplot(1,2,1)
# 仅显示坐标轴,但不显示刻度线
plt.xticks([])
plt.yticks([])
# 显示图片
plt.imshow(img1, aspect="auto")
plt.axis('on')
# 添加1行2列格子并添加第二个子格
ax2=fig.add_subplot(1, 2, 2)
# 添加自动布局
plt.tight_layout()
plt.xticks([])
plt.yticks([])
plt.imshow(img2, aspect="auto")
plt.axis('on')
# 调整四周和子图之间的间距
plt.subplots_adjust(left=0.005,right=0.995,bottom=0.005,top=0.995,wspace=0.010,hspace=0.1)
# 设置最大化
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()
参考网址: