# 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
import numpy as np
from mantidimaging.core.parallel import shared as ps
from mantidimaging.core.operations.base_filter import BaseFilter
from mantidimaging.gui.utility.qt_helpers import Type
if TYPE_CHECKING:
from mantidimaging.core.data import ImageStack
from mantidimaging.gui.windows.operations import FiltersWindowView
from PyQt5.QtWidgets import QComboBox, QDoubleSpinBox
[docs]
class RescaleFilter(BaseFilter):
"""Rescales the image data to a new [0, maximum output] range.
Intended to be used on: Any
When: Automatically used when saving as unsigned integer image formats, to avoid clipping negative values
"""
filter_name = 'Rescale'
[docs]
@staticmethod
def filter_func(images: ImageStack,
min_input: float = 0.0,
max_input: float = 10000.0,
max_output: float = 256.0,
progress=None) -> ImageStack:
"""
:param min_input: The Minimum value of the data that will be used.
Anything below this will be clipped to 0.
:param max_input: Maximum value of the data that will be used. Anything
above it will be clipped to 0.
:param max_output: Maximum value of the OUTPUT images. They will be
rescaled to range [0, MAX OUTPUT].
:return: The ImageStack object scaled to a new range.
"""
params = {'min_input': min_input, 'max_input': max_input, 'max_output': max_output}
ps.run_compute_func(RescaleFilter.compute_function, len(images.data), [images.shared_array], params)
return images
[docs]
@staticmethod
def compute_function(index: int, array: np.ndarray, params: dict):
min_input, max_input, max_output = params['min_input'], params['max_input'], params['max_output']
array[index] = RescaleFilter.filter_array(array[index], min_input, max_input, max_output)
[docs]
@staticmethod
def filter_array(image: np.ndarray, min_input: float, max_input: float, max_output: float) -> np.ndarray:
image[:] = np.interp(image, [min_input, max_input], [0, max_output])
return image
[docs]
@staticmethod
def register_gui(form, on_change, view: FiltersWindowView) -> dict[str, Any]:
from mantidimaging.gui.utility import add_property_to_form
_, min_input_widget = add_property_to_form('Min input',
Type.FLOAT,
form=form,
on_change=on_change,
valid_values=(-2147483647, 2147483647),
tooltip="Minimum value of the data that will be used.\n"
"Anything below this will be clipped to 0")
min_input_widget.setDecimals(8)
_, max_input_widget = add_property_to_form('Max input',
Type.FLOAT,
form=form,
on_change=on_change,
default_value=5.0,
valid_values=(-2147483647, 2147483647),
tooltip="Maximum value of the data that will be used.\n"
"Anything above it will be clipped to 0")
max_input_widget.setDecimals(8)
_, max_output_widget = add_property_to_form('Max output',
Type.FLOAT,
form=form,
on_change=on_change,
default_value=65535.0,
valid_values=(1, 2147483647),
tooltip="Maximum value of the OUTPUT images. They will \n"
"be rescaled to range [0, MAX OUTPUT]")
max_output_widget.setDecimals(8)
_, preset_widget = add_property_to_form('Preset',
Type.CHOICE,
form=form,
on_change=on_change,
valid_values=["Use values from above", "int8", "int16", "int32"],
tooltip="Provides pre-set ranges to rescale to.")
return {
'min_input_widget': min_input_widget,
'max_input_widget': max_input_widget,
'max_output_widget': max_output_widget,
'preset_widget': preset_widget
}
[docs]
@staticmethod
def execute_wrapper( # type: ignore
min_input_widget: QDoubleSpinBox, max_input_widget: QDoubleSpinBox, max_output_widget: QDoubleSpinBox,
preset_widget: QComboBox) -> partial:
min_input = min_input_widget.value()
max_input = max_input_widget.value()
max_output = max_output_widget.value()
if preset_widget.currentText() == "int8":
max_output = 255.0
elif preset_widget.currentText() == "int16":
max_output = 65535.0
elif preset_widget.currentText() == "int32":
max_output = 2147483647.0
return partial(RescaleFilter.filter_func, min_input=min_input, max_input=max_input, max_output=max_output)
[docs]
@staticmethod
def validate_execute_kwargs(kwargs: dict[str, Any]) -> bool:
return True