def normalize_stack(stack, mcp, dark_counts=100):
stack = stackify(stack)
mcp = imgify(mcp)
if not isinstance(dark_counts, (int, float, complex)):
dark_counts = imgify(dark_counts)
stack_normed = stack.copy()
for i, img in enumerate(progress_bar(stack, "Normalizing...")):
stack_normed[i] = normalize_image(img, mcp, dark_counts=dark_counts)
# is this monkey-patching necessary?:
stack_normed.mcp = mcp
stack_normed.dark_counts = dark_counts
return stack_normed
def normalize(img_or_stack, *args, **kwargs):
try:
img = imgify(img_or_stack)
return normalize_image(img, *args, **kwargs)
except FileNotFoundError:
stack = stackify(img_or_stack)
return normalize_stack(stack, *args, **kwargs)
def normalize_image(img, mcp, dark_counts=100):
img = imgify(img)
mcp = imgify(mcp)
if not isinstance(dark_counts, (int, float, complex)):
dark_image = imgify(dark_counts)
dark_counts = dark_image.data
img = img.copy()
try:
normed_mcp = np.clip(np.nan_to_num(mcp.data - dark_counts), 1, None)
normed = (img.data - dark_counts) / normed_mcp
except ValueError as e:
raise ValueError(
"Normalize: Resolution of MCP or dark image does not match."
) from e
img.data = np.nan_to_num(np.clip(normed, 0, None))
return img
def normalize(
self,
mcp: Image = None,
dark_counts: Union[int, float, Image] = 100,
inplace: bool = False,
) -> LEEMImg:
"""Normalization of LEEM Images
Parameters
----------
mcp : Image, optional
[description], by default None
dark_counts : Union[int, float, Image], optional
[description], by default 100
inplace : bool, optional
[description], by default False
Returns
-------
LEEMImg
[description]
"""
if mcp is None:
mcp = self.mcp # pylint: disable=access-member-before-definition
mcp = imgify(mcp)
if not isinstance(dark_counts, (int, float, complex)):
dark_counts = imgify(dark_counts)
result = np.nan_to_num((self - dark_counts) / (mcp - dark_counts))
if inplace:
self.image = result.image
self.mcp = mcp
self.dark_counts = dark_counts
return self
result.mcp = mcp
result.dark_counts = dark_counts
return result
def normalize(self,
mcp: Union[Image, str, None] = None,
inplace: bool = False,
**kwargs) -> LEEMStack:
"""
Normalization of images in stack
The images in the stack are normalized by appling Image.normalize(mcp) to each image
Parameters
----------
mcp : Image, str or None
Image or filename of image if str. If 'None' the mcp attribute of the images will be
used
inplace : bool, default False
If 'True' the stack itself will be normalized
If 'False' a copy of the stack will be normalized
**kwargs
Additional keyword arguments are passed through to Image.normalize
.. note:: Consider passing 'dark_counts' as a keyword argument, to specify non-default
dark counts of the images
Returns
-------
LEEMStack
LEEMStack with registered images. The stack itself is returned when 'inplace'=True
See Also
--------
LEEMImg.normalize
"""
# if not a copy funny things might happen when mcp is part of stack
mcp = imgify(mcp).copy()
if inplace:
stack = self
else:
stack = self.copy()
for img in tqdm(stack):
# if an image is multiple times in a stack and inplace is True, it should not be
# normalized twice, so if the mcp is already the current mcp, it will not be processed
if img.mcp is None or not img.mcp == mcp:
img.normalize(mcp=mcp, inplace=True, **kwargs)
return stack
def test_imgify(img, img_fname):
assert isinstance(utility.imgify(img), base.LEEMImg)
assert isinstance(utility.imgify(img_fname), base.LEEMImg)