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

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

Generally, the edges of an aligned image can become corrupted due interopolation artefacts. In this case, we can export a cropped region of interest by supplying the roi kwarg in the form [min_x_pixel, max_x_pixel, min_y_pixel, max_y_pixel]:

stack.export_tiff("aligned_cropped_stack.tiff", roi=[20, 280, 20, 180])