5. Correlated stacks

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Bluelake has the ability to export videos from the camera’s. These videos can be opened and sliced using CorrelatedStack:

stack = lk.CorrelatedStack("example.tiff")  # Loading a stack.
stack_slice = stack[2:10]  # Grab frame 2 to 9

You can also spatially crop to select a smaller region of interest:

stack_roi = stack.crop_by_pixels(10, 50, 20, 80)  # pixel coordinates as x_max, x_min, y_max, y_min

This can be useful, for instance, after applying color alignment to RGB images as the edges can become corrupted due to interpolation artifacts.

Full color RGB images are automatically reconstructed using the alignment matrices from Bluelake if available. This functionality can be turned off with the optional align keyword:

stack2 = lk.CorrelatedStack("example2.tiff", align=False)

Quite often, it is interesting to correlate events on the camera’s to channel data. To quickly explore the correlation between images in a CorrelatedStack and channel data you can use the following function:

# Making a plot where force is correlated to images in the stack.
stack.plot_correlated(file.force1x)

In some cases, additional processing may be needed, and we desire to have the data downsampled over the video frames. This can be done using the function Slice.downsampled_over using timestamps obtained from the CorrelatedStack:

# Determine the force trace averaged over frame 2...9.
file.force1x.downsampled_over(stack[2:10].timestamps)

The aligned image stack can also be exported to tiff format:

stack.export_tiff("aligned_stack.tiff")
stack[5:20].export_tiff("aligned_short_stack.tiff") # export a slice of the CorrelatedStack