Data Slicing using PyQtGraph
In this article, we will see how we can perform data slicing using PyQtGraph module in Python. 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.) and second is to provide tools to aid in rapid application development (for example, property trees such as used in Qt Designer).
In order to install the PyQtGraph we use the command given below
pip install pyqtgraph
A slice in a multidimensional array is a column of data corresponding to a single value for one or more members of the dimension. Slicing is the act of divvying up the cube to extract this information for a given slice. It is important because it helps the user visualize and gather information specific to a dimension. When you think of slicing, think of it as a specialized filter for a particular value in a dimension. A simple data-slicing task would be for given 3D data selecting a 2D plane and interpolate data along that plane to generate a slice image.
In order to do this, we have to do the following
- Import the required libraries like pyqtgraph, pyqt5 and numpy
- Create a main window class using pyqt5
- Create a graph window to add the widgets required to show the slicing
- Create two image view object in the layout, first to show the whole 3d data and second to show the slice
- Create a roi object and add it to the first image view to select the slice
- Create a 3d data and add it to the image view
- Connect a update method to the roi object when the region is changed, inside the update method get the region and set it to the second image view
- Add this graph window to the main window layout with any additional widgets.
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 * class Window(QMainWindow): def __init__( self ): super ().__init__() # setting title self .setWindowTitle( "PyQtGraph" ) # setting geometry self .setGeometry( 100 , 100 , 700 , 550 ) # 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() # text text = "Data Slicing" # creating a label label = QLabel(text) # setting minimum width label.setMinimumWidth( 130 ) # making label do word wrap label.setWordWrap( True ) # creating a window for graphs win = QMainWindow() # creating a widget object cwid = QWidget() # setting central widget to the graph window win.setCentralWidget(cwid) # creating a grid layout lay = QGridLayout() # setting grid layout to central widget of graphs cwid.setLayout(lay) # creating a image view objects imv1 = pg.ImageView() imv2 = pg.ImageView() # adding image view objects to the layout lay.addWidget(imv1, 0 , 0 ) lay.addWidget(imv2, 1 , 0 ) # creating a ROI object for selecting slice roi = pg.LineSegmentROI([[ 30 , 64 ], [ 100 , 64 ]], pen = 'r' ) # add roi to image view 1 imv1.addItem(roi) # creating 3d data # x value using numpy x1 = np.linspace( - 30 , 10 , 128 )[:, np.newaxis, np.newaxis] x2 = np.linspace( - 20 , 20 , 128 )[:, np.newaxis, np.newaxis] # y value using numpy y = np.linspace( - 30 , 10 , 128 )[np.newaxis, :, np.newaxis] z = np.linspace( - 20 , 20 , 128 )[np.newaxis, np.newaxis, :] # dimension 1 values d1 = np.sqrt(x1 * * 2 + y * * 2 + z * * 2 ) # dimension 2 values d2 = 2 * np.sqrt(x1[:: - 1 ] * * 2 + y * * 2 + z * * 2 ) # dimension 3 value d3 = 4 * np.sqrt(x2 * * 2 + y[:, :: - 1 ] * * 2 + z * * 2 ) # whole data ie all 3 dimensions data = (np.sin(d1) / d1 * * 2 ) + \ (np.sin(d2) / d2 * * 2 ) + (np.sin(d3) / d3 * * 2 ) # method to update the image view 2 def update(): # get the roi selected data from image view 1 d2 = roi.getArrayRegion(data, imv1.imageItem, axes = ( 1 , 2 )) # update the image view 2 data imv2.setImage(d2) # adding update method to the roi # when region is changed this method get called roi.sigRegionChanged.connect(update) # Display the data in both image view imv1.setImage(data) # setting the range of image view imv1.setHistogramRange( - 0.01 , 0.01 ) # setting levels of the image view imv1.setLevels( - 0.003 , 0.003 ) # call the update method update() # Creating a grid layout layout = QGridLayout() # minimum width value of the label label.setMinimumWidth( 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(win, 0 , 1 , 3 , 1 ) # setting this widget as central widget of the main widow self .setCentralWidget(widget) # create pyqt5 app App = QApplication(sys.argv) # create the instance of our Window window = Window() # start the app sys.exit(App. exec ()) |
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