Source code for mantidimaging.core.operations.gaussian.gaussian

# Copyright (C) 2023 ISIS Rutherford Appleton Laboratory UKRI
# SPDX - License - Identifier: GPL-3.0-or-later
from __future__ import annotations

from functools import partial
from logging import getLogger
from typing import TYPE_CHECKING

import scipy.ndimage as scipy_ndimage

from mantidimaging import helper as h
from mantidimaging.core.operations.base_filter import BaseFilter
from mantidimaging.core.parallel import shared as ps
from mantidimaging.core.utility.progress_reporting import Progress
from mantidimaging.gui.utility import add_property_to_form
from mantidimaging.gui.utility.qt_helpers import Type

    from import ImageStack

[docs]class GaussianFilter(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. """ filter_name = "Gaussian" link_histograms = True
[docs] @staticmethod def filter_func(data: ImageStack, size=None, mode=None, order=None, progress=None): """ :param data: Input data as a 3D numpy.ndarray :param size: Size of the kernel :param mode: The mode with which to handle the edges. One of [reflect, constant, nearest, mirror, wrap]. Modes are described in the `SciPy documentation <>`_. :param 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 :return: The processed 3D numpy.ndarray """ h.check_data_stack(data) if not size or not size > 1: raise ValueError(f'Size parameter must be greater than 1, but value provided was {size}') _execute(data, size, mode, order, progress) h.check_data_stack(data) return data
[docs] @staticmethod def register_gui(form, on_change, view): _, size_field = add_property_to_form('Kernel Size', Type.INT, 3, (2, 1000), form=form, on_change=on_change, tooltip="Size of the median filter kernel") _, order_field = add_property_to_form('Order', Type.INT, 0, (0, 3), form=form, on_change=on_change, tooltip="Order of the Gaussian filter") _, mode_field = add_property_to_form('Edge Mode', Type.CHOICE, valid_values=modes(), form=form, on_change=on_change, tooltip="Mode to handle the edges of the image") return {'size_field': size_field, 'order_field': order_field, 'mode_field': mode_field}
[docs] @staticmethod def execute_wrapper(size_field=None, order_field=None, mode_field=None): return partial(GaussianFilter.filter_func, size=size_field.value(), mode=mode_field.currentText(), order=order_field.value())
[docs]def modes(): return ['reflect', 'constant', 'nearest', 'mirror', 'wrap']
def _execute(images: ImageStack, size, mode, order, progress=None): log = getLogger(__name__) progress = Progress.ensure_instance(progress, task_name='Gaussian filter') f = ps.create_partial(scipy_ndimage.gaussian_filter, ps.return_to_self, sigma=size, mode=mode, order=order)"Starting PARALLEL gaussian filter, with pixel data type: {0}, " "filter size/width: {1}.".format(images.dtype, size)) progress.update() ps.execute(f, [images.shared_array],[0], progress, msg="Gaussian filter") progress.mark_complete()"Finished gaussian filter, with pixel data type: {0}, " "filter size/width: {1}.".format(images.dtype, size))