processed imageseries

Processed Image Series

This class is intended for image manipulations applied to all images of the imageseries. It is instantiated with an existing imageseries and a sequence of operations to be performed on each image. The class has built-in operations for common transformations and a mechanism for adding new operations. This class is typically used for preparing raw detector images for analysis, but other uses are possible. The rectangle operation is used in stats.percentile to compute percentiles one section at a time to avoid loading all images at once.

Instantiation

Here is an example:

oplist = [('dark', darkimg), ('flip', 'v')]
frames = range(2, len(ims))
pims = ProcessedImageSeries(ims, oplist, frame_list=frames)

Here, ims is an existing imageseries with two empty frames. The operation list has two operations. First, the a dark (background) image is subtracted. Then it is flipped about a vertical axis. Order is important here; operations do not always commute. Note that the dark image is usually constructed from the raw images, so if you flipped first, the dark subtraction would be wrong. Finally, the only keyword argument available is frame_list; it takes a sequence of frames. In the example, the first two frames are skipped.

Built-In Operations

The operation list is a sequence of (key, data) pairs. The key specifies the operation, and the data is passed with the image to the requested function. Here are the built-in functions by key.

• 'dark': dark subtraction; it's data is an image
• 'flip': these are simple image reorientations; the data is a short string; possible values are: - 'y' or 'v': flip about y-axis (vertical) - 'x' or 'h': flip about x-axis (horizontal) - 'vh','hv' or 'r180': 180 degree rotation - 't' or 'T': transpose - 'ccw90' or 'r90': rotate 90 degrees - 'cw90' or 'r270': rotate 270 Note there are possible shape changes in the last three, but most detector images are square.
• 'rectangle': restriction to a sub-rectangle of the image; data is a 2x2 array with each row giving a range of indices

Methods

In addition to the usual imageseries methods, there are:

@classmethod
def addop(cls, key, func):
    """Add operation to processing options

    *key* - string to use to specify this op
    *func* - function to call for this op: f(img, data)
    """
@property
def oplist(self):
    """list of operations to apply"""