Plot line over pyqtgraph.ImageView() - python-3.x

Question

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!

Answer 1

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()