hexrd.imageseries.stats module

aggregate statistics for imageseries

The functions here operate on the frames of an imageseries and return a single aggregate image. For each function, there is a corresponding iterable that allows you to run the function in smaller bits; the bits are either groups of frames or groups of rows, depending on the function. The iterable returns a sequence of images, the last being the final result.

For example:

# Using the standard function call img = stats.average(ims)

# Using the iterable with 10 chunks for img in stats.average_iter(ims, 10):

# update progress bar pass

NOTE: * Perhaps we should rename min -> minimum and max -> maximum to avoid

conflicting with the python built-ins

hexrd.imageseries.stats.average(ims, nframes=0)

average over frames

hexrd.imageseries.stats.average_iter(ims, nchunk, nframes=0)

average over frames

Note: average returns a float even if images are uint

hexrd.imageseries.stats.max(ims, nframes=0)

maximum over frames

hexrd.imageseries.stats.max_iter(ims, nchunk, nframes=0)

iterator for max function

hexrd.imageseries.stats.median(ims, nframes=0)

hexrd.imageseries.stats.median_iter(ims, nchunks, nframes=0, use_buffer=True)

hexrd.imageseries.stats.min(ims, nframes=0)

minimum over frames

hexrd.imageseries.stats.min_iter(ims, nchunk, nframes=0)

iterator for min function

hexrd.imageseries.stats.percentile(ims, pctl, nframes=0)

percentile function over frames

ims - the imageseries pctl - the percentile nframes - the number of frames to use (default/0 = all)

hexrd.imageseries.stats.percentile_iter(ims, pctl, nchunks, nframes=0, use_buffer=True)

iterator for percentile function