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Data Slicing using PyQtGraph

Last Updated : 13 Jan, 2022

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.

Output : 
 


 

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