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How to Efficiently Update Matplotlib Plots Without Overlaying?

Mary-Kate Olsen
Mary-Kate OlsenOriginal
2024-12-15 10:42:15634browse

How to Efficiently Update Matplotlib Plots Without Overlaying?

Updating Plots in Matplotlib

Redrawing plots in Matplotlib can be challenging, especially when you need to update them without appending additional plots. This question explores how to overcome this issue.

The problem stems from the use of Figure and FigureCanvasTkAgg, which creates a new plot every time the plots() function is called. This leads to multiple plots being overlaid on top of each other instead of being updated.

To resolve this, two options are available:

Option 1: Clear and Replot

This is the simplest option, but it is also the slowest. It involves clearing the existing plots before replotting the new data. This can be achieved by adding graph1.clear() and graph2.clear() to the beginning of the plots() function. While this approach is straightforward, it is computationally intensive and may not be suitable for real-time updates.

Option 2: Update Data

A more efficient approach is to update the data of the existing plot objects. This requires modifying the plots() function to update the ydata of the lines rather than creating new lines. This method is much faster but requires careful handling of data shape and axis limits.

For example:

# Update the y-data of the existing line
line1.set_ydata(np.sin(x + phase))
# Draw the updated plot
fig.canvas.draw()
# Flush any pending events
fig.canvas.flush_events()

This approach allows for efficient updates of the plot without the need to clear and replot the entire figure. It is particularly useful for real-time visualization of dynamic data.

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