def transform(
cls,
image: Image,
arguments: dict,
callback_function: Optional[Callable[[str, int],
None]] = None) -> Image:
keys = [x for x in arguments if x.startswith("scale")]
keys_order = Image.axis_order.lower()
scale_factor = [1.0] * len(keys_order)
if len(keys) == 1 and keys[0] == "scale":
for letter in image.get_dimension_letters().lower():
scale_factor[keys_order.index(letter)] = arguments["scale"]
spacing = [x / arguments["scale"] for x in image.spacing]
else:
# assume that all keys are in format scale_{}
for key in keys:
letter = key[-1]
scale_factor[keys_order.index(letter)] = arguments[key]
spacing = [
x / arguments[f"scale_{y}"]
for x, y in zip(image.spacing,
image.get_dimension_letters().lower())
]
array = zoom(image.get_data(), scale_factor, mode="mirror")
if image.mask is not None:
mask = zoom(image.mask, scale_factor[:-1], mode="mirror")
else:
mask = None
return image.substitute(data=array, image_spacing=spacing, mask=mask)
def __init__(self,
image: Image,
transform_dict: Dict[str, TransformBase] = None):
super().__init__()
if transform_dict is None:
transform_dict = image_transform_dict
self.choose = QComboBox()
self.stacked = QStackedWidget()
for key, val in transform_dict.items():
self.choose.addItem(key)
initial_values = val.calculate_initial(image)
form_widget = FormWidget(
val.get_fields_per_dimension(image.get_dimension_letters()),
initial_values)
self.stacked.addWidget(form_widget)
self.choose.currentIndexChanged.connect(self.stacked.setCurrentIndex)
self.cancel_btn = QPushButton("Cancel")
self.cancel_btn.clicked.connect(self.reject)
self.process_btn = QPushButton("Process")
self.process_btn.clicked.connect(self.process)
self.transform_dict = transform_dict
self.result_val: ImageAdjustTuple = None
layout = QGridLayout()
layout.addWidget(self.choose, 0, 0, 1, 3)
layout.addWidget(self.stacked, 1, 0, 1, 3)
layout.addWidget(self.cancel_btn, 2, 0)
layout.addWidget(self.process_btn, 2, 2)
self.setLayout(layout)
def calculate_initial(cls, image: Image):
min_val = min(image.spacing)
return {
f"scale_{l}": x / min_val
for x, l in zip(image.spacing,
image.get_dimension_letters().lower())
}
