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PyQtGraph – Auto Adjust the size of of Image View

  • Last Updated : 24 Oct, 2020

In this article, we will see how we can auto adjust the size of the image view object in PyQTGaph. PyQtGraph is a graphics and user interface library for Python that provides functionality commonly required in designing and science applications. Its primary goals are to provide fast, interactive graphics for displaying data (plots, video, etc.). Widget used for display and analysis of image data. Implements many features like displaying 2D and 3D image data. For 3D data, a z-axis slider is displayed allowing the user to select which frame is displayed. Displays histogram of image data with a movable region defining the dark/light levels, editable gradient provides a color lookup table. Auto adjust property will resize the image view according to the content of it, the new size will be according to the size of the content.
We can create an image view with the help of the command given below 

# creating a pyqtgraph image view object
imv = pg.ImageView()

Syntax: ImageView(parent=None, name=’ImageView’, view=None, imageItem=None, levelMode=’mono’, *args)

Parameters:

  • parent (QWidget): Specifies the parent widget to which this ImageView will belong. If None, then the ImageView is created with no parent.
  • name (str): The name used to register both the internal ViewBox and the PlotItem used to display ROI data.
  • view (ViewBox or PlotItem): If specified, this will be used as the display area that contains the displayed image.
  • imageItem (ImageItem): If specified, this object will be used to display the image. Must be an instance of ImageItem or other compatible object.
  • levelMode: specifies the *levelMode* argument

Returns: Object of class ImageView
 

In order to do this we use adjustSize() method with the image view object



Syntax : imv.adjustSize()
Argument : It takes no argument
Return : It returns None 
 

Below is the implementation 

Python3




# importing Qt widgets
from PyQt5.QtWidgets import *
  
# importing system
import sys
  
# importing numpy as np
import numpy as np
  
# importing pyqtgraph as pg
import pyqtgraph as pg
from PyQt5.QtGui import *
from PyQt5.QtCore import *
  
# Image View class
class ImageView(pg.ImageView):
  
    # constructor which inherit original
    # ImageView
    def __init__(self, *args, **kwargs):
        pg.ImageView.__init__(self, *args, **kwargs)
  
class Window(QMainWindow):
  
    def __init__(self):
        super().__init__()
  
        # setting title
        self.setWindowTitle("PyQtGraph")
  
        # setting geometry
        self.setGeometry(100, 100, 600, 500)
  
        # icon
        icon = QIcon("skin.png")
  
        # setting icon to the window
        self.setWindowIcon(icon)
  
        # calling method
        self.UiComponents()
  
        # showing all the widgets
        self.show()
  
    # method for components
    def UiComponents(self):
  
        # creating a widget object
        widget = QWidget()
  
        # creating a label
        label = QLabel("Geeksforgeeks Image View")
  
        # setting minimum width
        label.setMinimumWidth(130)
  
        # making label do word wrap
        label.setWordWrap(True)
  
        # setting configuration options
        pg.setConfigOptions(antialias = True)
  
        # creating image view view object
        imv = ImageView()
  
        # Create random 3D data set with noisy signals
        img = pg.gaussianFilter(np.random.normal(size=(200, 200)), 
                                (5, 5)) * 20 + 100
  
        # setting new axis to image
        img = img[np.newaxis, :, :]
  
        # decay data
        decay = np.exp(-np.linspace(0, 0.3, 100))[:, np.newaxis, np.newaxis]
  
        # random data
        data = np.random.normal(size=(100, 200, 200))
        data += img * decay
        data += 2
  
        # adding time-varying signal
        sig = np.zeros(data.shape[0])
        sig[30:] += np.exp(-np.linspace(1, 10, 70))
        sig[40:] += np.exp(-np.linspace(1, 10, 60))
        sig[70:] += np.exp(-np.linspace(1, 10, 30))
  
        sig = sig[:, np.newaxis, np.newaxis] * 3
        data[:, 50:60, 30:40] += sig
  
        # setting image to image view
        # Displaying the data and assign each frame a time value from 1.0 to 3.0
        imv.setImage(data, xvals=np.linspace(1., 3., data.shape[0]))
  
        # Set a custom color map
        colors = [
            (0, 0, 0),
            (4, 5, 61),
            (84, 42, 55),
            (15, 87, 60),
            (208, 17, 141),
            (255, 255, 255)
        ]
  
        # color map
        cmap = pg.ColorMap(pos=np.linspace(0.0, 1.0, 6), color = colors)
  
        # setting color map to the image view
        imv.setColorMap(cmap)
  
        # Creating a grid layout
        layout = QGridLayout()
  
        # minimum width value of the label
        label.setFixedWidth(130)
  
        # setting this layout to the widget
        widget.setLayout(layout)
  
        # adding label in the layout
        layout.addWidget(label, 1, 0)
  
        # plot window goes on right side, spanning 3 rows
        layout.addWidget(imv, 0, 1, 3, 1)
  
        # setting this widget as central widget of the main widow
        self.setCentralWidget(widget)
  
        # auto adjust size of image view
        imv.adjustSize()
  
# create pyqt5 app
App = QApplication(sys.argv)
  
# create the instance of our Window
window = Window()
  
# start the app
sys.exit(App.exec())

Output : 
 

 

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