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.
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In order to do this, we have to do the followingÂ
- 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 widgetsfrom PyQt5.QtWidgets import *Â
# importing systemimport sysÂ
# importing numpy as npimport numpy as npÂ
# importing pyqtgraph as pgimport pyqtgraph as pgfrom PyQt5.QtGui import *from PyQt5.QtCore import *Â
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class Window(QMainWindow):Â
    def __init__(self):        super().__init__()Â
        # setting title        self.setWindowTitle("PyQtGraph")Â
        # setting geometry        self.setGeometry(100, 100, 700, 550)Â
        # icon        icon = QIcon("skin.png")Â
        # setting icon to the window        self.setWindowIcon(icon)Â
        # calling method        self.UiComponents()Â
        # showing all the widgets        self.show()Â
    # method for components    def UiComponents(self):Â
        # creating a widget object        widget = QWidget()Â
        # text        text = "Data Slicing"Â
        # creating a label        label = QLabel(text)Â
        # setting minimum width        label.setMinimumWidth(130)Â
        # making label do word wrap        label.setWordWrap(True)Â
        # creating a window for graphs        win = QMainWindow()Â
        # creating a widget object        cwid = QWidget()Â
        # setting central widget to the graph window        win.setCentralWidget(cwid)Â
        # creating a grid layout        lay = QGridLayout()Â
        # setting grid layout to central widget of graphs        cwid.setLayout(lay)Â
        # creating a image view objects        imv1 = pg.ImageView()        imv2 = pg.ImageView()Â
        # adding image view objects to the layout        lay.addWidget(imv1, 0, 0)        lay.addWidget(imv2, 1, 0)Â
        # creating a ROI object for selecting slice        roi = pg.LineSegmentROI([[30, 64], [100, 64]], pen='r')Â
        # add roi to image view 1        imv1.addItem(roi)Â
        # 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]Â
        # y value using numpy        y = np.linspace(-30, 10, 128)[np.newaxis, :, np.newaxis]        z = np.linspace(-20, 20, 128)[np.newaxis, np.newaxis, :]Â
        # dimension 1 values        d1 = np.sqrt(x1 ** 2 + y ** 2 + z ** 2)Â
        # dimension 2 values        d2 = 2 * np.sqrt(x1[::-1] ** 2 + y ** 2 + z ** 2)Â
        # dimension 3 value        d3 = 4 * np.sqrt(x2 ** 2 + y[:, ::-1] ** 2 + z ** 2)Â
        # whole data ie all 3 dimensions        data = (np.sin(d1) / d1 ** 2) + \            (np.sin(d2) / d2 ** 2) + (np.sin(d3) / d3 ** 2)Â
        # method to update the image view 2        def update():Â
            # get the roi selected data from image view 1            d2 = roi.getArrayRegion(data, imv1.imageItem, axes=(1, 2))Â
            # update the image view 2 data            imv2.setImage(d2)Â
        # adding update method to the roi        # when region is changed this method get called        roi.sigRegionChanged.connect(update)Â
        # Display the data in both image view        imv1.setImage(data)Â
        # setting the range of image view        imv1.setHistogramRange(-0.01, 0.01)Â
        # setting levels of the image view        imv1.setLevels(-0.003, 0.003)Â
        # call the update method        update()Â
        # Creating a grid layout        layout = QGridLayout()Â
        # minimum width value of the label        label.setMinimumWidth(130)Â
        # setting this layout to the widget        widget.setLayout(layout)Â
        # adding label in the layout        layout.addWidget(label, 1, 0)Â
        # plot window goes on right side, spanning 3 rows        layout.addWidget(win, 0, 1, 3, 1)Â
        # setting this widget as central widget of the main widow        self.setCentralWidget(widget)Â
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# create pyqt5 appApp = QApplication(sys.argv)Â
# create the instance of our Windowwindow = Window()Â
# start the appsys.exit(App.exec()) |
Output :Â
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