ITV-visual is a Python module to visualize selected signals of a workbook in a variety of plots. The package offers a static and an interactive version of a pairplot, distribution plots, line plots and violin plots. After applying the necessary data transformations, the former plots are a practical and direct way of understanding the distribution of the data per parameter and identifying their relationships. The module includes a user interface (UI) designed to interact with the Seeq server. Specifically, the UI can be installed as an Add-on Tool in Seeq Workbench.
Developed by Omar Bayomie
Introduction.mp4
pip install + git+https://github.com/itvizion/seeq-itvizion-visualization.git ''' The backend of ITV-visual requires Python 3.7 or later.
See requirements.txt file for a list of
dependencies and versions. Additionally, you will need to install the seeq module with the appropriate version that
matches your Seeq server. For more information on the seeq module see seeq at pypi
If you want to install ITV-visual as a Seeq Add-on Tool, you will need:
- Seeq Data Lab (>= R52.1.5, >=R53.0.2, or >=R54)
seeqmodule whose version matches the Seeq server version- Seeq administrator access
- Enable Add-on Tools in the Seeq server
The latest build of the project can be found here as a wheel file. The file is published as a courtesy to the user, and it does not imply any obligation for support from the publisher.
- Create a new Seeq Data Lab project and open the Terminal window
- Run
pip install ITV-visualor contact support@itvizion.com - Import and use preferred classes in your python scripts by providing only the workbook url
or use directly as an add-on through the preferred seeq workbook.
A general overview of the motivation for, benefits and functionality of the toolbox, as implemented in IT Vizion Visualization toolbox, is provided in this section. A guide for browsing through and using each plot is presented below.
The Violin plot class initializes an object that builds a GUI for an analysis worksheet provided through its URL. The GUI displays a violin plot, distribution plot and line plot of available signals.
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| Figure 1. User Interface of the Violin plot add-on. |
Through the interface, the user has the ability to select multiple signals by holding the CTRL button and clicking or using the Shift button and keyboard arrows, or select all using the checkbox right below.
Furthermore, the "Sampling Interval" field provides for an interval to sample the signals' data. The user can fill the field using a variety of options, from seconds, to days and months. Then, the start and end date of the data need to be selected.
Finally, the last two checkboxes provide for: - Normalize data: data of each signal are subtracted their mean and divided by their standard deviation in order to bring them to a scale that allows for plotting them together in the same figure. - Plot Distribution: histograms including their mean value are generated for each signal.
On the plot, the user can hover over the violin plot in order to access calculations such as the mean, standard deviation, kernel density estimation and other. The user will also be able to zoom in and out, hide signals, download the figures and more, using the buttons on the top right corner.
Lastly, a static line plot is generated for all the plots and shown at the bottom of the output.
Violin.Plot.MOV
The Pairplot_interactive class initializes an object that builds a GUI for an analysis worksheet provided through its URL. The GUI displays a pairplot of available signals and allows users to select signals, generate plots and colour by the desired string column.
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| Figure 2. User Interface of the Interactive Pairplot add-on. |
Through the interface, the user has the ability to select multiple signals by holding the CTRL button and clicking or using the Shift button and keyboard arrows, or select all using the checkbox right below.
Furthermore, the "Sampling Interval" field provides for an interval to sample the signals' data. The user can fill the field using a variety of options, from seconds, to days and months. Then, the start and end date of the data need to be selected.
After clicking the plotting button, if lexical expressions/string values are present in the data from the different signals, the add-on recognizes them and provides for a selection box that would colour the plot by the different values of the selected signal.
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| Figure 3. Colour by option for string values. |
On the plot, the user can hover over the violin plot in order to access the values at selected points. The user will also be able to zoom in and out, hide signals, download the figures and more, using the buttons on the top right corner.
Interactive.pair.plot.MOV
The Pairplot class initializes an object that builds a GUI for an analysis worksheet provided through its URL. The GUI displays a static pairplot and line plot of available signals and allows users to select signals, generate plots and colour by the desired string column.
 |
| Figure 4. User Interface of the Static Pairplot add-on. |
Through the interface, the user has the ability to select multiple signals by holding the CTRL button and clicking or using the Shift button and keyboard arrows, or select all using the checkbox right below.
Furthermore, the "Sampling Interval" field provides for an interval to sample the signals' data. The user can fill the field using a variety of options, from seconds, to days and months. Then, the start and end date of the data need to be selected.
After clicking the plotting button, if lexical expressions/string values are present in the data from the different signals, the add-on recognizes them and provides for a selection box that would colour the plot by the different values of the selected signal.
|
| Figure 5. Colour by option for string values. |
Lastly, a static line plot is generated for all the plots and shown at the bottom of the output.
Pair.Plot.mov
The Violinplot class initializes an object that builds a GUI for an analysis worksheet provided through its URL. The GUI displays a violin plot, distribution plot and line plot of available signals.
Through the interface, the user has the ability to select multiple signals (holding the CTRL button and clicking or using the Shift button and keyboard arrows) to visualize and either generate the violin plots in separate figures or plot on the same figure by clicking on the option to normalize the data. Violin plots include certain calculations such as the mean, standard deviation, kernel density estimation and other. The user will also be able to zoom in and out, hide signals, download the figures and more.
The Pairplot_interactive class initializes an object that builds a GUI for an analysis worksheet provided through its URL. The GUI displays a pairplot of available signals and allows users to select signals, generate plots and colour by the desired string column.
Through the interface, the user has the ability to select multiple signals (holding the CTRL button and clicking or using the Shift button and keyboard arrows) to visualize. The user will also be able to zoom in and out, hide signals, download the figures and more.
The Pairplot class initializes an object that builds a GUI for an analysis worksheet provided through its URL. The GUI displays a static pairplot and line plot of available signals and allows users to select signals, generate plots and colour by the desired string column. Through the interface, the user has the ability to select multiple signals (holding the CTRL button and clicking or using the Shift button and keyboard arrows) to visualize.