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python-3.xpyqt5numpy-ndarrayqwidget

Plot line over pyqtgraph.ImageView()


I am using Pyqt5 to plot some medical images (numpy arrays) in three different widgets. Now, I want to plot a line over the image (displayed using pg.ImageViewer). Have someone already done this?

Thanks!


Solution

  • You can access the viewbox of the pg.ImageView widget using .getView(). From there you can add any items to it that you like using viewbox.AddItem(). Below is a modified version of the ImageView example which plots a line plot on the ImageView.

    # -*- coding: utf-8 -*-
    """
    This example demonstrates the use of ImageView with 3-color image stacks.
    ImageView is a high-level widget for displaying and analyzing 2D and 3D data.
    ImageView provides:
    
      1. A zoomable region (ViewBox) for displaying the image
      2. A combination histogram and gradient editor (HistogramLUTItem) for
         controlling the visual appearance of the image
      3. A timeline for selecting the currently displayed frame (for 3D data only).
      4. Tools for very basic analysis of image data (see ROI and Norm buttons)
    
    """
    ## Add path to library (just for examples; you do not need this)
    import initExample
    
    import numpy as np
    from pyqtgraph.Qt import QtCore, QtGui
    import pyqtgraph as pg
    
    # Interpret image data as row-major instead of col-major
    pg.setConfigOptions(imageAxisOrder='row-major')
    
    app = pg.mkQApp("ImageView Example")
    
    ## Create window with ImageView widget
    win = QtGui.QMainWindow()
    win.resize(800,800)
    imv = pg.ImageView()
    
    imv_v = imv.getView()
    
    
    win.setCentralWidget(imv)
    win.show()
    win.setWindowTitle('pyqtgraph example: ImageView')
    
    ## Create random 3D data set with time varying signals
    dataRed = np.ones((100, 200, 200)) * np.linspace(90, 150, 100)[:, np.newaxis, np.newaxis]
    dataRed += pg.gaussianFilter(np.random.normal(size=(200, 200)), (5, 5)) * 100
    dataGrn = np.ones((100, 200, 200)) * np.linspace(90, 180, 100)[:, np.newaxis, np.newaxis]
    dataGrn += pg.gaussianFilter(np.random.normal(size=(200, 200)), (5, 5)) * 100
    dataBlu = np.ones((100, 200, 200)) * np.linspace(180, 90, 100)[:, np.newaxis, np.newaxis]
    dataBlu += pg.gaussianFilter(np.random.normal(size=(200, 200)), (5, 5)) * 100
    
    data = np.concatenate(
        (dataRed[:, :, :, np.newaxis], dataGrn[:, :, :, np.newaxis], dataBlu[:, :, :, np.newaxis]), axis=3
    )
    
    
    ## Display 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]))
    
    '''ADDED CODE'''
    imv_v = imv.getView()
    pci = pg.PlotCurveItem(x=[1,50,100,150,200], y=[1,50,100,150,200])
    imv_v.addItem(pci)
    ''''''
    
    ## Set a custom color map
    colors = [
        (0, 0, 0),
        (45, 5, 61),
        (84, 42, 55),
        (150, 87, 60),
        (208, 171, 141),
        (255, 255, 255)
    ]
    cmap = pg.ColorMap(pos=np.linspace(0.0, 1.0, 6), color=colors)
    imv.setColorMap(cmap)
    
    # Start up with an ROI
    imv.ui.roiBtn.setChecked(True)
    imv.roiClicked()
    
    if __name__ == '__main__':
        pg.exec()