绘图未使用 matplotlib 中的按钮小部件根据用户输入进行更新

Question

我有一个 matplotlib 图，我想根据用户输入进行更新。用户为三个参数输入三个值，并根据这三个输入构建一条路径。然后，该算法获取该路径目录中的每个图像，过度混合所有图像并显示它们。

该算法通常运行良好（无需用户输入），但现在，绘图似乎永远不会更新。然而，路径是根据输入正确构建的。我通过每次单击更新按钮时打印新路径来检查这一点。

这是我的代码：

import matplotlib.pyplot as plt
import ipywidgets as widgets
from IPython.display import display
import numpy as np

# Function to update the plot based on button clicks
def update_plot(param1, param2, param3):
   # Construct the path based on the selected values and the image filename based on slider 
   positions
   path = f'C:/Users/Jeff/Desktop/images/{param1}mL VE-Wasser + {param2} L Stickstoff +{param3} W'

   new_path = path + '/*.JPG'
    
   # Create list to later save the individual segmented images
   segmented_imgs = []

   for image in glob.glob(new_path):

       # Add all segmented images to a list of images (their numpy arrays)
       segmented_img = prepare_images()
       segmented_imgs.append(segmented_img)

   # Get the overblended final image
   overblended_img = sum(segmented_imgs)

   # Divide pixel intesities by number of images to get back to scale 0 to 1
   overblended_img = overblended_img / len(segmented_imgs)

   # Plot spraying cone with different regions integrated over the image series (overblended)
   plt.figure(figsize=(10, 12))
   plt.imshow(overblended_img)

# Create interactive widgets for each parameter
param1_widget = widgets.Text(value='', description='Medium in mL/min:')
param2_widget = widgets.Text(value='', description='Gas in L/min:')
param3_widget = widgets.Text(value='', description='Leistung in W:')

# Create a button to update the plot update_button = widgets.Button(description="Update Plot")

# Define the callback function for the button
def on_button_clicked(b):
    update_plot(param1_widget.value, param2_widget.value, param3_widget.value)

update_button.on_click(on_button_clicked)

# Display the widgets and button
display(param1_widget, param2_widget, param3_widget, update_button)

Answer 1

我不能确定，因为问题中的示例不可重现，但似乎每次更新绘图时您都会创建一个新图形。将行

plt.figure(figsize=(10, 12))

移到

update_plot

函数之外，仅创建一次。

import matplotlib.pyplot as plt
import ipywidgets as widgets
from IPython.display import display
import numpy as np

# Function to update the plot based on button clicks
def update_plot(param1, param2, param3):
   # Construct the path based on the selected values and the image filename based on slider 
   positions
   path = f'C:/Users/Jeff/Desktop/images/{param1}mL VE-Wasser + {param2} L Stickstoff +{param3} W'

   new_path = path + '/*.JPG'
    
   # Create list to later save the individual segmented images
   segmented_imgs = []

   for image in glob.glob(new_path):

       # Add all segmented images to a list of images (their numpy arrays)
       segmented_img = prepare_images()
       segmented_imgs.append(segmented_img)

   # Get the overblended final image
   overblended_img = sum(segmented_imgs)

   # Divide pixel intesities by number of images to get back to scale 0 to 1
   overblended_img = overblended_img / len(segmented_imgs)

   # Plot spraying cone with different regions integrated over the image series (overblended)
   # CHANGED - Don't create a new figure here
   plt.imshow(overblended_img)

# Create interactive widgets for each parameter
param1_widget = widgets.Text(value='', description='Medium in mL/min:')
param2_widget = widgets.Text(value='', description='Gas in L/min:')
param3_widget = widgets.Text(value='', description='Leistung in W:')

# Create a button to update the plot update_button = widgets.Button(description="Update Plot")

# Define the callback function for the button
def on_button_clicked(b):
    update_plot(param1_widget.value, param2_widget.value, param3_widget.value)

update_button.on_click(on_button_clicked)

# CHANGED - Create the figure only once e.g. down here
fig = plt.figure(figsize=(10, 12))

# Display the widgets and button
display(param1_widget, param2_widget, param3_widget, update_button)