Adding different plots
There are three different plot types:
- time series plot
- scatter plot
- map plot
You can add them using the 'ADD PLOT' button
Time series plot
The Time series plot is the standard plot type in Marple. Therefore it’s the most versatile! This might be obvious but time series plots allow you to visualise data that was recorded over time.
Within Marple time series plots, you can visualise multiple signals in one plot. This is also the goal of the platform. We want to show correlation between signals as good as possible.
Adding plots: You can however add multiple plots under each other. This can be useful if you want to visualise a lot of signals at the same time and you want to keep your visualisation more organised. To do so click the ADD PLOT button on the top right of the platform.
Arranging the plots: When adding a new plot window to your visualisation, Marple will automatically arrange it under the old time series plot. You can however change the arrangment of the plots. You can do that as follows:
- Click the lock button on the top right
- You can now drag the borders (that are now red) of the plot windows to reshape the plots
- You can also drag the plots around
Time series toolbar
From left to right you can do multiple things with the toolbar:
- Change the colour of the selected visualised signal
- Change the line style of the selected visualised signal
- Change the limits of the selected visualised signal: you can find more about it here. In short, it’s the max and min value of the y-axis for this specific signal
- The reset limits button: see the signal limits section on the Analysis page
- The link limits button: see the signal limits section on the Analysis page
- The functions button: This button allows you to do post-processing on the data and create calculated functions. See the calculated functions section for more information
- Two buttons that move the signal up and down the list of visualised signals and to the back and front of the visualisation.
- The events button: To toggle the events function on or off. Events allow you to add certain event information as a dot on the time series graph. (This feature is not yet available)
- The auto y-scaling button allows you to zoom n on the y-axis without needing to change the limits settings. see the signal limits section on the Analysis page
- The export plot button allows you to make a nice export of your visualisation.
- Reset all zoom levels button: See the zooming section on the Analysis page for more info.
The scatter plot will automatically appear as an extra plot on the bottom of your screen. Feel free to resize it to your liking!
Initially a scatter plot looks quite empty, quite obvious as there are no signals selected yet.
You can drag the signals from the signal list (on your left!) to either the x-axis or y-axis of the scatter plot. Once you have selected some data it might look like this:
There are a few options I will discuss in detail.
- Fit X-axis: by default, the scatter will dynamically change the range of the x-axis in order to fit the data.
- Buckets: Choose to display buckets (squares) instead of dots. This can be sued to make a heatmap of your data
- Limits: When highlighting a signal, you can change the range of how the signal is displayed. For a signal on the y-axis this will change the y-axis range. For a signal on the x-axis this will change the x-axis range. Note that when ‘Fit X-axis’ is enabled, you cannot change the limits of the x-axis signal.
- Up/down arrow: When multiple signals are displayed on the y-axis, change the overlay order
- Swap X & Y: Using this button you can quickly switch around the x and y axis signals.
A few closing remarks:
- The scatter plot will display the data of the time range that is selected in the time series plot, or from the zoom bar at the very top of Marple.
- In order to keep a smooth web-based experience, we need to subsample the data. This might cause your data to look a bit ‘fat’. You can change the resolution in settings.
- Scatter plots can currently only be made of signals that have the same time base
Goal: The aim of map plot is to geographically represent and visualise data (on an Open Street Map background by default).
That allows you, for instance, to quickly preview where data behaves in a certain way during a test.
Requirements: To use the map plot feature you will need to import latitude and longitude data expressed in degrees and be present in the same file as your other signals.
Zoom and focus: By zooming in and/or isolating data on the timeseries window, Marple will automatically display the corresponding data on the map plot window.
You can even be more precise by selecting a specific time with the cursor on the timeseries plot and see the corresponding position on the map plot.
Of course you can simply zoom in and out on the map as well.
Full trajectory: When zoomed in on the time series plot the corresponding points on the map are highlighted. To display points on the map outside the time series zoom level in grey or not show them at all. toggle this button.
Home button: to quickly reach or come back to default zoom level, click on the home button.
Cursor focus: allow you to focus the zoom on your cursor
Custom background: you can add a custom background by selecting the custom map button, then upload your own background. To do this you will need to define the grid of your custom background.
The Fast Fourier Transform plot type (or FFT plot) is a special one. It allows you to add a signal to it and make an FFT of that signal in an instant.
The logic of this is well known by now:
- In the Analysis part of Marple: click on the dropdown next to the add plot button and select “Frequency”
- An empty FFT plot will appear in your current active tab
- To add a signal to the plot drag and drop it from the signal list all the way on the left of the analysis view
In the toolbar above the plot, you can do the following:
- Change the color of the plot
- Add a frequency range (zooming in on the x-axis)
- Change the y-axis to a logarithmic scale (effectively changing it from amplitude to db)
- Turn the FFT into a Power Spectral Density plot
- Remove a DC offset