mantidimaging.core.operations.gaussian.gaussian module¶
- class mantidimaging.core.operations.gaussian.gaussian.GaussianFilter[source]¶
Bases:
BaseFilter
Applies Gaussian filter to the data.
Intended to be used on: Projections or reconstructed slices
When: As a pre-processing or post-reconstruction step to reduce noise.
- static execute_wrapper(size_field=None, order_field=None, mode_field=None)[source]¶
Should construct a partial call to _filter_func using values taken from the widgets passed to this function as kwargs. :param kwargs: widgets which contain values required for _filter_func. :return: a partial call to _filter_func using parameters taken from the input widgets.
- static filter_func(data: Images, size=None, mode=None, order=None, cores=None, chunksize=None, progress=None)[source]¶
- Parameters:
data – Input data as a 3D numpy.ndarray
size – Size of the kernel
mode – The mode with which to handle the edges. One of [reflect, constant, nearest, mirror, wrap]. Modes are described in the SciPy documentation.
order – The order of the filter along each axis is given as a sequence of integers, or as a single number. An order of 0 corresponds to convolution with a Gaussian kernel. An order of 1, 2, or 3 corresponds to convolution with the first, second or third derivatives of a Gaussian. Higher order derivatives are not implemented
cores – The number of cores that will be used to process the data.
chunksize – The number of chunks that each worker will receive.
- Returns:
The processed 3D numpy.ndarray
- filter_name = 'Gaussian'¶
- link_histograms = True¶
- static register_gui(form, on_change, view)[source]¶
Adds any required input widgets to the given form and returns references to them.
The return values should be in a dict which can be unpacked as kwargs for a call to the operations execute_wrapper.
- Parameters:
view –
form – the layout to create input widgets in
on_change – the filter view action to be bound to all created inputs
- Returns:
the widgets bound as kwargs which are needed to call execute_wrapper