9468539832

Committed 11 Jun 2024 03:14PM UTC coverage: 72.705% (-0.01%) from 72.716%

Build # 9468539832

Build Type

push

github

Committed by

web-flow

Commit Message

Compute mon norm (#2093)

Run Details

1919 of 3233 branches covered (59.36%)

Branch coverage included in aggregate %.

6 of 6 new or added lines in 1 file covered. (100.0%)

2 existing lines in 2 files now uncovered.

9540 of 12528 relevant lines covered (76.15%)

0.76 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

97.44

/mantidimaging/core/operations/monitor_normalisation/monitor_normalisation.py

# Copyright (C) 2024 ISIS Rutherford Appleton Laboratory UKRI
# SPDX - License - Identifier: GPL-3.0-or-later
from __future__ import annotations
from functools import partial
from typing import Any, TYPE_CHECKING
from collections.abc import Callable

import numpy as np

from mantidimaging.core.operations.base_filter import BaseFilter
from mantidimaging.core.parallel import shared as ps

if TYPE_CHECKING:
    from mantidimaging.core.data import ImageStack
    from mantidimaging.gui.mvp_base import BaseMainWindowView
    from PyQt5.QtWidgets import QFormLayout, QWidget


def _divide_by_counts(data=None, counts=None):
    data[:] = np.true_divide(data, counts)


class MonitorNormalisation(BaseFilter):
    """Normalises the image data using the average count of a beam monitor from the
    experiment log file. This scaling operation is an alternative to ROI normalisation
    and allows to account for beam fluctuations and different exposure times of projections.

    Intended to be used on: Projections

    When: As a pre-processing step to normalise the grey value ranges of the data.
    """
    filter_name = "Monitor Normalisation"
    link_histograms = True

    @staticmethod
    def filter_func(images: ImageStack, progress=None) -> ImageStack:
        """
        :return: The ImageStack object which has been normalised.
        """
        if images.num_projections == 1:
            # we can't really compute the preview as the image stack copy
            # passed in doesn't have the logfile in it
            raise RuntimeError("No logfile available for this stack.")

        counts = images.counts()
        if counts is None:
            raise RuntimeError("No loaded log values for this stack.")

        normalization_factor = counts.value / counts.value[0]
        params = {'normalization_factor': normalization_factor}

        ps.run_compute_func(MonitorNormalisation.compute_function, images.data.shape[0], images.shared_array, params,
                            progress)
        return images

    @staticmethod
    def compute_function(i: int, array: np.ndarray, params: dict[str, np.ndarray]):
        array[i] /= params['normalization_factor'][i]

    @staticmethod
    def register_gui(form: QFormLayout, on_change: Callable, view: BaseMainWindowView) -> dict[str, QWidget]:
        return {}

    @staticmethod
    def execute_wrapper(*args) -> partial:
        return partial(MonitorNormalisation.filter_func)

    @staticmethod
    def validate_execute_kwargs(kwargs: dict[str, Any]) -> bool:
        return True

1	# Copyright (C) 2024 ISIS Rutherford Appleton Laboratory UKRI
2	# SPDX - License - Identifier: GPL-3.0-or-later
3	from __future__ import annotations	1✔
4	from functools import partial	1✔
5	from typing import Any, TYPE_CHECKING	1✔
6	from collections.abc import Callable	1✔
7
8	import numpy as np	1✔
9
10	from mantidimaging.core.operations.base_filter import BaseFilter	1✔
11	from mantidimaging.core.parallel import shared as ps	1✔
12
13	if TYPE_CHECKING:
14	from mantidimaging.core.data import ImageStack
15	from mantidimaging.gui.mvp_base import BaseMainWindowView
16	from PyQt5.QtWidgets import QFormLayout, QWidget
17
18
19	def _divide_by_counts(data=None, counts=None):	1✔
UNCOV 20	data[:] = np.true_divide(data, counts)	×
21
22
23	class MonitorNormalisation(BaseFilter):	1✔
24	"""Normalises the image data using the average count of a beam monitor from the
25	experiment log file. This scaling operation is an alternative to ROI normalisation
26	and allows to account for beam fluctuations and different exposure times of projections.
27
28	Intended to be used on: Projections
29
30	When: As a pre-processing step to normalise the grey value ranges of the data.
31	"""
32	filter_name = "Monitor Normalisation"	1✔
33	link_histograms = True	1✔
34
35	@staticmethod	1✔
36	def filter_func(images: ImageStack, progress=None) -> ImageStack:	1✔
37	"""
38	:return: The ImageStack object which has been normalised.
39	"""
40	if images.num_projections == 1:	1✔
41	# we can't really compute the preview as the image stack copy
42	# passed in doesn't have the logfile in it
43	raise RuntimeError("No logfile available for this stack.")	1✔
44
45	counts = images.counts()	1✔
46	if counts is None:	1✔
47	raise RuntimeError("No loaded log values for this stack.")	1✔
48
49	normalization_factor = counts.value / counts.value[0]	1✔
50	params = {'normalization_factor': normalization_factor}	1✔
51
52	ps.run_compute_func(MonitorNormalisation.compute_function, images.data.shape[0], images.shared_array, params,	1✔
53	progress)
54	return images	1✔
55
56	@staticmethod	1✔
57	def compute_function(i: int, array: np.ndarray, params: dict[str, np.ndarray]):	1✔
58	array[i] /= params['normalization_factor'][i]	1✔
59
60	@staticmethod	1✔
61	def register_gui(form: QFormLayout, on_change: Callable, view: BaseMainWindowView) -> dict[str, QWidget]:	1✔
62	return {}	1✔
63
64	@staticmethod	1✔
65	def execute_wrapper(*args) -> partial:	1✔
66	return partial(MonitorNormalisation.filter_func)	1✔
67
68	@staticmethod	1✔
69	def validate_execute_kwargs(kwargs: dict[str, Any]) -> bool:	1✔
70	return True	1✔

mantidproject / mantidimaging / 9468539832

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous