Skip to content
Related Articles

Related Articles

Improve Article

PyQtGraph – Setting Predefined Gradient to Image View

  • Last Updated : 25 Oct, 2020

In this article, we will see how we can set a predefined gradient to 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 movable region defining the dark/light levels, editable gradient provides a color lookup table, frame slider may also be moved using left/right arrow keys as well as pgup, pgdn, home, and end. In computer graphics, a color gradient specifies a range of position-dependent colors, usually used to fill a region. For example, many window managers allow the screen background to be specified as a gradient.

Below is the list of predefined gradients available

‘thermal’, ‘flame’, ‘yellowy’, ‘bipolar’, ‘spectrum’, ‘cyclic’, ‘greyclip’, ‘grey’, ‘viridis’, ‘inferno’, ‘plasma’, ‘magma’

We can create an image view with the help of the command given below 

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

In order to do this we use setPredefinedGradient method with the image view object
Syntax : imv.setPredefinedGradient(name)
Argument : It takes string as 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()
  
        # setting fixed size of window
        self.setFixedSize(QSize(600, 500))
  
    # 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)
  
        # setting predefined gradient to image view
        imv.setPredefinedGradient('plasma')
  
  
# create pyqt5 app
App = QApplication(sys.argv)
  
# create the instance of our Window
window = Window()
  
# start the app
sys.exit(App.exec())

Output:

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course




My Personal Notes arrow_drop_up
Recommended Articles
Page :