def __init__(self, json_path):
super().__init__()
self.current_segmentation_dict = "default"
self.segmentation_dict = ProfileDict()
self.json_folder_path = json_path
self.last_executed_algorithm = ""
self.history: List[HistoryElement] = []
self.history_index = -1
def test_dump_custom_types(self):
prof_dict = ProfileDict()
prof_dict.set("a.b.c", 1)
data = {"a": RadiusType.R2D, "b": prof_dict}
text = json.dumps(data, cls=ProfileEncoder)
loaded = json.loads(text, object_hook=profile_hook)
assert loaded["a"] == RadiusType.R2D
assert loaded["b"].get("a.b.c") == 1
def __init__(self):
super().__init__()
self.color_map = []
self.border_val = []
self.current_profile_dict = "default"
self.view_settings_dict = ProfileDict()
self.colormap_dict = ColormapDict(self.get_from_profile("custom_colormap", {}))
self.label_color_dict = LabelColorDict(self.get_from_profile("custom_label_colors", {}))
self.cached_labels: Optional[Tuple[str, np.ndarray]] = None
def test_serialize(self, tmp_path):
dkt = ProfileDict()
dkt.set("a.b.c", 1)
dkt.set("a.b.a", 2)
with open(tmp_path / "test.json", "w") as f_p:
json.dump(dkt, f_p, cls=ProfileEncoder)
with open(tmp_path / "test.json") as f_p:
dkt2 = json.load(f_p, object_hook=profile_hook)
assert dkt.my_dict == dkt2.my_dict
def __init__(self, json_path):
super().__init__(json_path)
self._mask = None
self.compare_segmentation = None
self.segmentation_pipelines_dict = ProfileDict()
self.segmentation_profiles_dict = ProfileDict()
self.batch_plans_dict = ProfileDict()
self.measurement_profiles_dict = ProfileDict()
def __init__(self,
json_path: Union[Path, str],
profile_name: str = "default"):
"""
:param json_path: path to store
:param profile_name: name of profile to be used. default value is "default"
"""
super().__init__()
napari_path = os.path.dirname(json_path) if os.path.basename(
json_path) in ["analysis", "mask"] else json_path
self.napari_settings: "NapariSettings" = napari_get_settings(
napari_path)
self._current_roi_dict = profile_name
self._roi_dict = ProfileDict()
self.json_folder_path = json_path
self.last_executed_algorithm = ""
self.history: List[HistoryElement] = []
self.history_index = -1
self.last_executed_algorithm = ""
self._points = None
def __init__(self, json_path, profile_name="default"):
super().__init__(json_path, profile_name)
self._mask = None
self.compare_segmentation = None
self._segmentation_pipelines_dict = ProfileDict()
self._segmentation_profiles_dict = ProfileDict()
self._batch_plans_dict = ProfileDict()
self._measurement_profiles_dict = ProfileDict()
self._segmentation_profiles_dict.connect(
"", self.roi_profiles_changed.emit, maxargs=0)
self._segmentation_pipelines_dict.connect(
"", self.roi_pipelines_changed.emit, maxargs=0)
self._measurement_profiles_dict.connect(
"", self.measurement_profiles_changed.emit, maxargs=0)
self._batch_plans_dict.connect("",
self.batch_plans_changed.emit,
maxargs=0)
def test_update(self):
dkt = ProfileDict()
dkt.update(a=1, b=2, c=3)
assert dkt.my_dict == {"a": 1, "b": 2, "c": 3}
dkt2 = ProfileDict()
dkt2.update(c=4, d={"a": 2, "e": 7})
assert dkt2.get("d.e") == 7
dkt.update(dkt2)
assert dkt.get("d.e") == 7
assert dkt.get("c") == 4
dkt.update({"g": 1, "h": 4})
assert dkt.get("g") == 1
dkt.update({"w": 1, "z": 4}, w=3)
assert dkt.get("w") == 3
assert dkt.verify_data()
assert dkt.filter_data() == []
dkt.set("e.h.l", {"aaa": 1, "__error__": True})
assert not dkt.verify_data()
assert dkt.filter_data() == ["e.h"]
def test_simple(self):
dkt = ProfileDict()
dkt.set("a.b.c", 1)
dkt.set("a.b.a", 2)
assert dkt.get("a.b.c") == 1
with pytest.raises(KeyError):
dkt.get("a.b.d")
dkt.get("a.b.d", 3)
assert dkt.get("a.b.d") == 3
assert dkt.get("a.b") == {"a": 2, "c": 1, "d": 3}
with pytest.raises(TypeError):
dkt.set("a.b.c.d", 3)
class PartSettings(BaseSettings):
"""
last_executed_algorithm - parameter for caring last used algorithm
"""
compare_segmentation_change = Signal(ROIInfo)
json_encoder_class = PartEncoder
load_metadata = staticmethod(load_metadata)
last_executed_algorithm: str
save_locations_keys = [
"open_directory",
"save_directory",
"export_directory",
"batch_plan_directory",
"multiple_open_directory",
]
def __init__(self, json_path):
super().__init__(json_path)
self._mask = None
self.compare_segmentation = None
self.segmentation_pipelines_dict = ProfileDict()
self.segmentation_profiles_dict = ProfileDict()
self.batch_plans_dict = ProfileDict()
self.measurement_profiles_dict = ProfileDict()
def fix_history(self, algorithm_name, algorithm_values):
"""
set new algorithm parameters to
:param str algorithm_name:
:param dict algorithm_values:
"""
self.history[self.history_index +
1] = self.history[self.history_index +
1].replace_(segmentation_parameters={
"algorithm_name": algorithm_name,
"values": algorithm_values
})
@staticmethod
def cmp_history_element(el1: HistoryElement, el2: HistoryElement):
return el1.mask_property == el2.mask_property
def set_segmentation_to_compare(self, segmentation: ROIInfo):
self.compare_segmentation = segmentation
self.compare_segmentation_change.emit(segmentation)
@property
def use_physical_unit(self):
return self.get("use_physical_unit", False)
def set_use_physical_unit(self, value):
self.set("use_physical_unit", value)
def _image_changed(self):
super()._image_changed()
self._mask = None
def get_project_info(self) -> ProjectTuple:
algorithm_name = self.last_executed_algorithm
if algorithm_name:
algorithm_val = {
"algorithm_name": algorithm_name,
"values": deepcopy(self.get(f"algorithms.{algorithm_name}")),
}
else:
algorithm_val = {}
return ProjectTuple(
file_path=self.image.file_path,
image=self.image.substitute(),
roi=self.roi,
roi_info=self.roi_info,
additional_layers=self.additional_layers,
mask=self.mask,
history=self.history[:self.history_index + 1],
algorithm_parameters=algorithm_val,
)
def set_project_info(self, data: typing.Union[ProjectTuple, MaskInfo]):
if isinstance(data, ProjectTuple):
if self.image.file_path == data.image.file_path and self.image.shape == data.image.shape:
if data.roi is not None:
try:
self.image.fit_array_to_image(data.roi)
self.mask = data.mask
except ValueError:
self.image = data.image.substitute()
else:
self.mask = data.mask
else:
self.image = data.image.substitute(mask=data.mask)
self.roi = data.roi
self._additional_layers = data.additional_layers
self.set_history(data.history[:])
if data.algorithm_parameters:
self.last_executed_algorithm = data.algorithm_parameters[
"algorithm_name"]
self.set(f"algorithms.{self.last_executed_algorithm}",
deepcopy(data.algorithm_parameters["values"]))
self.algorithm_changed.emit()
elif isinstance(data, MaskInfo):
self.mask = data.mask_array
def get_save_list(self) -> typing.List[SaveSettingsDescription]:
return super().get_save_list() + [
SaveSettingsDescription("segmentation_pipeline_save.json",
self.segmentation_pipelines_dict),
SaveSettingsDescription("segmentation_profiles_save.json",
self.segmentation_profiles_dict),
SaveSettingsDescription("statistic_profiles_save.json",
self.measurement_profiles_dict),
SaveSettingsDescription("batch_plans_save.json",
self.batch_plans_dict),
]
@property
def segmentation_pipelines(self) -> typing.Dict[str, SegmentationPipeline]:
return self.segmentation_pipelines_dict.get(self._current_roi_dict, {})
@property
def segmentation_profiles(self) -> typing.Dict[str, ROIExtractionProfile]:
return self.segmentation_profiles_dict.get(self._current_roi_dict, {})
@property
def batch_plans(self) -> typing.Dict[str, CalculationPlan]:
return self.batch_plans_dict.get(self._current_roi_dict, {})
@property
def measurement_profiles(self) -> typing.Dict[str, MeasurementProfile]:
return self.measurement_profiles_dict.get(self._current_roi_dict, {})
class BaseSettings(ViewSettings):
"""
:ivar json_folder_path: default location for saving/loading settings data
:ivar last_executed_algorithm: name of last executed algorithm.
:cvar save_locations_keys: list of names of distinct save location.
location are stored in "io"
"""
mask_changed = Signal()
points_changed = Signal()
request_load_files = Signal(list)
""":py:class:`~.Signal` mask changed signal"""
json_encoder_class = ProfileEncoder
load_metadata = staticmethod(load_metadata_base)
algorithm_changed = Signal()
""":py:class:`~.Signal` emitted when current algorithm should be changed"""
save_locations_keys = []
def __init__(self,
json_path: Union[Path, str],
profile_name: str = "default"):
"""
:param json_path: path to store
:param profile_name: name of profile to be used. default value is "default"
"""
super().__init__()
napari_path = os.path.dirname(json_path) if os.path.basename(
json_path) in ["analysis", "mask"] else json_path
self.napari_settings: "NapariSettings" = napari_get_settings(
napari_path)
self._current_roi_dict = profile_name
self._roi_dict = ProfileDict()
self.json_folder_path = json_path
self.last_executed_algorithm = ""
self.history: List[HistoryElement] = []
self.history_index = -1
self.last_executed_algorithm = ""
self._points = None
def _image_changed(self):
super()._image_changed()
self.points = None
@property
def points(self):
return self._points
@points.setter
def points(self, value):
self._points = value if value is not None else None
self.points_changed.emit()
@property
def theme_name(self) -> str:
try:
theme = self.napari_settings.appearance.theme
if self.get_from_profile("first_start", True):
theme = "light"
self.napari_settings.appearance.theme = theme
self.set_in_profile("first_start", False)
return theme
except AttributeError: # pragma: no cover
return "light"
@theme_name.setter
def theme_name(self, value: str):
self.napari_settings.appearance.theme = value
def set_segmentation_result(self, result: ROIExtractionResult):
if (result.file_path is not None and result.file_path != "" and
result.file_path != self.image.file_path): # pragma: no cover
if self._parent is not None:
# TODO change to non disrupting popup
QMessageBox().warning(
self._parent, "Result file bug",
"It looks like one try to set ROI form another file.")
return
if result.info_text and self._parent is not None:
QMessageBox().information(self._parent, "Algorithm info",
result.info_text)
self._additional_layers = result.additional_layers
self.last_executed_algorithm = result.parameters.algorithm
self.set(f"algorithms.{result.parameters.algorithm}",
result.parameters.values)
# Fixme not use EventedDict here
try:
roi_info = result.roi_info.fit_to_image(self.image)
except ValueError: # pragma: no cover
raise ValueError(ROI_NOT_FIT)
if result.points is not None:
self.points = result.points
self._roi_info = roi_info
self.roi_changed.emit(self._roi_info)
def _load_files_call(self, files_list: List[str]):
self.request_load_files.emit(files_list)
def add_history_element(self, elem: HistoryElement) -> None:
self.history_index += 1
if self.history_index < len(self.history) and self.cmp_history_element(
elem, self.history[self.history_index]):
self.history[self.history_index] = elem
else:
self.history = self.history[:self.history_index]
self.history.append(elem)
def history_size(self) -> int:
return self.history_index + 1
def history_redo_size(self) -> int:
if self.history_index + 1 == len(self.history):
return 0
return len(self.history[self.history_index + 1:])
def history_redo_clean(self) -> None:
self.history = self.history[:self.history_size()]
def history_current_element(self) -> HistoryElement:
return self.history[self.history_index]
def history_next_element(self) -> HistoryElement:
return self.history[self.history_index + 1]
def history_pop(self) -> Optional[HistoryElement]:
if self.history_index != -1:
self.history_index -= 1
return self.history[self.history_index + 1]
return None
def set_history(self, history: List[HistoryElement]):
self.history = history
self.history_index = len(self.history) - 1
def get_history(self) -> List[HistoryElement]:
return self.history[:self.history_index + 1]
@staticmethod
def cmp_history_element(el1, el2):
return False
@property
def mask(self):
return self._image.mask
@mask.setter
def mask(self, value):
try:
self._image.set_mask(value)
self.mask_changed.emit()
except ValueError:
raise ValueError("mask do not fit to image")
def get_save_list(self) -> List[SaveSettingsDescription]:
"""List of files in which program save the state."""
return [
SaveSettingsDescription("segmentation_settings.json",
self._roi_dict),
SaveSettingsDescription("view_settings.json",
self.view_settings_dict),
]
def get_path_history(self) -> List[str]:
"""
return list containing last 10 elements added with :py:meth:`.add_path_history` and
last opened in each category form :py:attr:`save_location_keys`
"""
res = self.get(DIR_HISTORY, [])[:]
for name in self.save_locations_keys:
val = self.get("io." + name, str(Path.home()))
if val not in res:
res = res + [val]
return res
@staticmethod
def _add_elem_to_list(data_list: list, value: Any, keep_len=10) -> list:
try:
data_list.remove(value)
except ValueError:
data_list = data_list[:keep_len - 1]
return [value] + data_list
def get_last_files(self) -> List[Tuple[Tuple[Union[str, Path], ...], str]]:
return self.get(FILE_HISTORY, [])
def add_load_files_history(self, file_path: Sequence[Union[str, Path]],
load_method: str): # pragma: no cover
warnings.warn("`add_load_files_history` is deprecated",
FutureWarning,
stacklevel=2)
return self.add_last_files(file_path, load_method)
def add_last_files(self, file_path: Sequence[Union[str, Path]],
load_method: str):
self.set(
FILE_HISTORY,
self._add_elem_to_list(self.get(FILE_HISTORY, []),
[list(file_path), load_method]))
# keep list of files as list because json serialize tuple to list
self.add_path_history(os.path.dirname(file_path[0]))
def get_last_files_multiple(
self) -> List[Tuple[Tuple[Union[str, Path], ...], str]]:
return self.get(MULTIPLE_FILES_OPEN_HISTORY, [])
def add_last_files_multiple(self, file_paths: List[Union[str, Path]],
load_method: str):
self.set(
MULTIPLE_FILES_OPEN_HISTORY,
self._add_elem_to_list(self.get(MULTIPLE_FILES_OPEN_HISTORY, []),
[list(file_paths), load_method],
keep_len=30),
)
# keep list of files as list because json serialize tuple to list
self.add_path_history(os.path.dirname(file_paths[0]))
def add_path_history(self, dir_path: Union[str, Path]):
"""Save path in history of visited directories. Store only 10 last"""
dir_path = str(dir_path)
self.set(DIR_HISTORY,
self._add_elem_to_list(self.get(DIR_HISTORY, []), dir_path))
def set(self, key_path: str, value):
"""
function for saving general state (not visualization). This is accessor to
:py:meth:`~.ProfileDict.set` of inner variable.
:param key_path: dot separated path
:param value: value to store. The value need to be json serializable.
"""
self._roi_dict.set(f"{self._current_roi_dict}.{key_path}", value)
def get(self, key_path: str, default=None):
"""
Function for getting general state (not visualization). This is accessor to
:py:meth:`~.ProfileDict.get` of inner variable.
:param key_path: dot separated path
:param default: default value if key is missed
"""
return self._roi_dict.get(f"{self._current_roi_dict}.{key_path}",
default)
def connect_(self, key_path, callback):
# TODO fixme fix when introduce switch profiles
self._roi_dict.connect(key_path, callback)
def dump_part(self, file_path, path_in_dict, names=None):
data = self.get(path_in_dict)
if names is not None:
data = {name: data[name] for name in names}
os.makedirs(os.path.dirname(file_path), exist_ok=True)
with open(file_path, "w", encoding="utf-8") as ff:
json.dump(data, ff, cls=self.json_encoder_class, indent=2)
@classmethod
def load_part(cls, file_path):
data = cls.load_metadata(file_path)
bad_key = []
if isinstance(data, MutableMapping) and not check_loaded_dict(data):
for k, v in data.items():
if not check_loaded_dict(v):
bad_key.append(k)
for el in bad_key:
del data[el]
elif isinstance(data, ProfileDict) and not data.verify_data():
bad_key = data.filter_data()
return data, bad_key
def dump(self, folder_path: Union[Path, str, None] = None):
"""
Save current application settings to disc.
:param folder_path: path to directory in which data should be saved.
If is None then use :py:attr:`.json_folder_path`
"""
if self.napari_settings.save is not None:
self.napari_settings.save()
else:
self.napari_settings._save() # pylint: disable=W0212
if folder_path is None:
folder_path = self.json_folder_path
if not os.path.exists(folder_path):
os.makedirs(folder_path)
errors_list = []
for el in self.get_save_list():
try:
dump_string = json.dumps(el.values,
cls=self.json_encoder_class,
indent=2)
with open(os.path.join(folder_path, el.file_name),
"w",
encoding="utf-8") as ff:
ff.write(dump_string)
except Exception as e: # pylint: disable=W0703
errors_list.append((e, os.path.join(folder_path,
el.file_name)))
if errors_list:
logger.error(errors_list)
return errors_list
def load(self, folder_path: Union[Path, str, None] = None):
"""
Load settings state from given directory
:param folder_path: path to directory in which data should be saved.
If is None then use :py:attr:`.json_folder_path`
"""
if folder_path is None:
folder_path = self.json_folder_path
errors_list = []
for el in self.get_save_list():
file_path = os.path.join(folder_path, el.file_name)
if not os.path.exists(file_path):
continue
error = False
try:
data: ProfileDict = self.load_metadata(file_path)
if not data.verify_data():
errors_list.append((file_path, data.filter_data()))
error = True
el.values.update(data)
except Exception as e: # pylint: disable=W0703
error = True
errors_list.append((file_path, e))
finally:
if error:
timestamp = datetime.today().strftime("%Y-%m-%d_%H_%M_%S")
base_path, ext = os.path.splitext(file_path)
os.rename(file_path, base_path + "_" + timestamp + ext)
if errors_list:
logger.error(errors_list)
return errors_list
def get_project_info(self) -> ProjectInfoBase:
"""Get all information needed to save project"""
raise NotImplementedError # pragma: no cover
def set_project_info(self, data: ProjectInfoBase):
"""Set project info"""
raise NotImplementedError # pragma: no cover
@staticmethod
def verify_image(image: Image, silent=True) -> Union[Image, bool]:
if image.is_time:
if image.is_stack:
raise TimeAndStackException()
if silent:
return image.swap_time_and_stack()
raise SwapTimeStackException()
return True
class ViewSettings(ImageSettings):
colormap_changes = Signal()
labels_changed = Signal()
theme_changed = Signal()
profile_data_changed = Signal(str, object)
"""Signal about changes in stored data (set with set_in_profile)"""
def __init__(self):
super().__init__()
self.color_map = []
self.border_val = []
self.current_profile_dict = "default"
self.view_settings_dict = ProfileDict()
self.colormap_dict = ColormapDict(
self.get_from_profile("custom_colormap", {}))
self.label_color_dict = LabelColorDict(
self.get_from_profile("custom_label_colors", {}))
self.cached_labels: Optional[Tuple[str, np.ndarray]] = None
@property
def theme_name(self) -> str:
"""Name of current theme."""
return self.get_from_profile("theme", "light")
@property
def theme(self):
"""Theme as structure."""
try:
return get_theme(self.theme_name, as_dict=False)
except TypeError: # pragma: no cover
theme = get_theme(self.theme_name)
return Namespace(
**{
k: Color(v)
if isinstance(v, str) and v.startswith("rgb") else v
for k, v in theme.items()
})
@property
def style_sheet(self):
"""QSS style sheet for current theme."""
with warnings.catch_warnings():
warnings.simplefilter("ignore", FutureWarning)
theme = get_theme(self.theme_name)
# TODO understand qss overwrite mechanism
return napari_template(
"\n".join(register.qss_list) + get_stylesheet() +
"\n".join(register.qss_list), **theme)
@theme_name.setter
def theme_name(self, value: str):
"""Name of current theme."""
if value not in napari.utils.theme.available_themes():
raise ValueError(
f"Unsupported theme {value}. Supported one: {self.theme_list()}"
)
if value == self.theme_name:
return
self.set_in_profile("theme", value)
self.theme_changed.emit()
@staticmethod
def theme_list():
"""Sequence of available themes"""
try:
return napari.utils.theme.available_themes()
except: # noqa: E722 # pylint: disable=W0702 # pragma: no cover
return ("light", )
@property
def chosen_colormap(self):
"""Sequence of selected colormap to be available in dropdown"""
data = self.get_from_profile("colormaps", starting_colors[:])
res = [x for x in data if x in self.colormap_dict]
if len(res) != data:
if not res:
res = starting_colors[:]
self.set_in_profile("colormaps", res)
return res
@chosen_colormap.setter
def chosen_colormap(self, val):
self.set_in_profile("colormaps", val)
self.colormap_changes.emit()
@property
def current_labels(self):
"""Current labels scheme for marking ROI"""
return self.get_from_profile("labels_used", "default")
@current_labels.setter
def current_labels(self, val):
if val not in self.label_color_dict:
raise ValueError(f"Unknown label scheme name '{val}'")
self.set_in_profile("labels_used", val)
self.labels_changed.emit()
@property
def label_colors(self):
key = self.current_labels
if key not in self.label_color_dict:
key = "default"
self.current_labels = key
if not (self.cached_labels and key == self.cached_labels[0]):
self.cached_labels = key, self.label_color_dict.get_array(key)
return self.cached_labels[1]
def chosen_colormap_change(self, name, visibility):
colormaps = set(self.chosen_colormap)
if visibility:
colormaps.add(name)
else:
with suppress(KeyError):
colormaps.remove(name)
# TODO update sorting rule
self.chosen_colormap = list(
sorted(colormaps, key=self.colormap_dict.get_position))
def get_channel_info(
self,
view: str,
num: int,
default: Optional[str] = None) -> str: # pragma: no cover
warnings.warn(
"get_channel_info is deprecated, use get_channel_colormap_name instead",
category=DeprecationWarning,
stacklevel=2,
)
return self.get_channel_colormap_name(view, num, default)
def get_channel_colormap_name(self,
view: str,
num: int,
default: Optional[str] = None) -> str:
cm = self.chosen_colormap
if default is None:
default = cm[num % len(cm)]
resp = self.get_from_profile(f"{view}.cmap.num{num}", default)
if resp not in self.colormap_dict:
resp = cm[num % len(cm)]
self.set_in_profile(f"{view}.cmap.num{num}", resp)
return resp
def set_channel_info(self, view: str, num, value: str): # pragma: no cover
warnings.warn(
"set_channel_info is deprecated, use set_channel_colormap_name instead",
category=DeprecationWarning,
stacklevel=2,
)
self.set_channel_colormap_name(view, num, value)
def set_channel_colormap_name(self, view: str, num, value: str):
self.set_in_profile(f"{view}.cmap.num{num}", value)
def connect_channel_colormap_name(self, view: str, fun: Callable):
self.connect_to_profile(f"{view}.cmap", fun)
@property
def available_colormaps(self):
return list(self.colormap_dict.keys())
def _image_changed(self):
self.border_val = self.image.get_ranges()
super()._image_changed()
def change_profile(self, name):
self.current_profile_dict = name
self.view_settings_dict.profile_change()
def set_in_profile(self, key_path, value):
"""
Function for saving information used in visualization. This is accessor to
:py:meth:`~.ProfileDict.set` of inner variable.
:param key_path: dot separated path
:param value: value to store. The value need to be json serializable."""
self.view_settings_dict.set(f"{self.current_profile_dict}.{key_path}",
value)
self.profile_data_changed.emit(key_path, value)
def get_from_profile(self, key_path, default=None):
"""
Function for getting information used in visualization. This is accessor to
:py:meth:`~.ProfileDict.get` of inner variable.
:param key_path: dot separated path
:param default: default value if key is missed
"""
return self.view_settings_dict.get(
f"{self.current_profile_dict}.{key_path}", default)
def connect_to_profile(self, key_path, callback):
# TODO fixme fix when introduce switch profiles
self.view_settings_dict.connect(key_path, callback)
def test_callback(self):
def dummy_call():
receiver.dummy()
receiver = MagicMock()
dkt = ProfileDict()
dkt.connect("", receiver.empty)
dkt.connect("", dummy_call)
dkt.connect("b", receiver.b)
dkt.connect(["d", "c"], receiver.dc)
dkt.set("test.a", 1)
assert receiver.empty.call_count == 1
assert receiver.dummy.call_count == 1
receiver.empty.assert_called_with("a")
receiver.dummy.assert_called_with()
dkt.set("test.a", 1)
assert receiver.empty.call_count == 1
receiver.b.assert_not_called()
dkt.set("test2.a", 1)
assert receiver.empty.call_count == 2
receiver.b.assert_not_called()
dkt.set(["test", "b"], 1)
assert receiver.empty.call_count == 3
assert receiver.b.call_count == 1
dkt.set("test.d.c", 1)
receiver.dc.assert_called_once()
dkt.set("test.a", 2)
assert receiver.empty.call_count == 5
class BaseSettings(ViewSettings):
"""
:ivar json_folder_path: default location for saving/loading settings data
:ivar last_executed_algorithm: name of last executed algorithm.
:cvar save_locations_keys: list of names of distinct save location.
location are stored in "io"
"""
mask_changed = Signal()
mask_representation_changed = Signal()
""":py:class:`~.Signal` mask changed signal"""
json_encoder_class = ProfileEncoder
load_metadata = staticmethod(load_metadata_base)
algorithm_changed = Signal()
""":py:class:`~.Signal` emitted when current algorithm should be changed"""
save_locations_keys = []
def __init__(self, json_path):
super().__init__()
self.current_segmentation_dict = "default"
self.segmentation_dict = ProfileDict()
self.json_folder_path = json_path
self.last_executed_algorithm = ""
self.history: List[HistoryElement] = []
self.history_index = -1
def mask_representation_changed_emit(self):
self.mask_representation_changed.emit()
def add_history_element(self, elem: HistoryElement) -> None:
self.history_index += 1
if self.history_index < len(self.history) and self.cmp_history_element(
elem, self.history[self.history_index]):
self.history[self.history_index] = elem
else:
self.history = self.history[:self.history_index]
self.history.append(elem)
def history_size(self) -> int:
return self.history_index + 1
def history_redo_size(self) -> int:
if self.history_index + 1 == len(self.history):
return 0
return len(self.history[self.history_index + 1:])
def history_redo_clean(self) -> None:
self.history = self.history[:self.history_size()]
def history_current_element(self) -> HistoryElement:
return self.history[self.history_index]
def history_next_element(self) -> HistoryElement:
return self.history[self.history_index + 1]
def history_pop(self) -> Optional[HistoryElement]:
if self.history_index != -1:
self.history_index -= 1
return self.history[self.history_index + 1]
return None
def set_history(self, history: List[HistoryElement]):
self.history = history
self.history_index = len(self.history) - 1
def get_history(self) -> List[HistoryElement]:
return self.history[:self.history_index + 1]
@staticmethod
def cmp_history_element(el1, el2):
return False
@property
def mask(self):
return self._image.mask
@mask.setter
def mask(self, value):
try:
self._image.set_mask(value)
self.mask_changed.emit()
except ValueError:
raise ValueError("mask do not fit to image")
def get_save_list(self) -> List[SaveSettingsDescription]:
"""List of files in which program save the state."""
return [
SaveSettingsDescription("segmentation_settings.json",
self.segmentation_dict),
SaveSettingsDescription("view_settings.json",
self.view_settings_dict),
]
def get_path_history(self) -> List[str]:
"""
return list containing last 10 elements added with :py:meth:`.add_path_history` and
last opened in each category form :py:attr:`save_location_keys`
"""
res = self.get("io.history", [])[:]
for name in self.save_locations_keys:
val = self.get("io." + name, str(Path.home()))
if val not in res:
res = res + [val]
return res
def add_path_history(self, dir_path: str):
"""Save path in history of visited directories. Store only 10 last"""
history: List[str] = self.get("io.history", [])
try:
history.remove(dir_path)
except ValueError:
history = history[:9]
self.set("io.history", [dir_path] + history[-9:])
def set(self, key_path: str, value):
"""
function for saving general state (not visualization). This is accessor to
:py:meth:`~.ProfileDict.set` of inner variable.
:param key_path: dot separated path
:param value: value to store. The value need to be json serializable.
"""
self.segmentation_dict.set(
f"{self.current_segmentation_dict}.{key_path}", value)
def get(self, key_path: str, default=None):
"""
Function for getting general state (not visualization). This is accessor to
:py:meth:`~.ProfileDict.get` of inner variable.
:param key_path: dot separated path
:param default: default value if key is missed
"""
return self.segmentation_dict.get(
f"{self.current_segmentation_dict}.{key_path}", default)
def dump_part(self, file_path, path_in_dict, names=None):
data = self.get(path_in_dict)
if names is not None:
data = {name: data[name] for name in names}
with open(file_path, "w") as ff:
json.dump(data, ff, cls=self.json_encoder_class, indent=2)
def load_part(self, file_path):
data = self.load_metadata(file_path)
bad_key = []
if isinstance(data, dict):
if not check_loaded_dict(data):
for k, v in data.items():
if not check_loaded_dict(v):
bad_key.append(k)
for el in bad_key:
del data[el]
elif isinstance(data, ProfileDict):
if not data.verify_data():
bad_key = data.filter_data()
return data, bad_key
def dump(self, folder_path: Optional[str] = None):
"""
Save current application settings to disc.
:param folder_path: path to directory in which data should be saved.
If is None then use :py:attr:`.json_folder_path`
"""
if folder_path is None:
folder_path = self.json_folder_path
if not os.path.exists(folder_path):
os.makedirs(folder_path)
errors_list = []
for el in self.get_save_list():
try:
dump_string = json.dumps(el.values,
cls=self.json_encoder_class,
indent=2)
with open(os.path.join(folder_path, el.file_name), "w") as ff:
ff.write(dump_string)
except Exception as e:
errors_list.append((e, os.path.join(folder_path,
el.file_name)))
if errors_list:
print(errors_list, file=sys.stderr)
return errors_list
def load(self, folder_path: Optional[str] = None):
"""
Load settings state from given directory
:param folder_path: path to directory in which data should be saved.
If is None then use :py:attr:`.json_folder_path`
"""
if folder_path is None:
folder_path = self.json_folder_path
errors_list = []
for el in self.get_save_list():
file_path = os.path.join(folder_path, el.file_name)
if not os.path.exists(file_path):
continue
error = False
try:
data: ProfileDict = self.load_metadata(file_path)
if not data.verify_data():
errors_list.append((file_path, data.filter_data()))
error = True
el.values.update(data)
except Exception as e:
error = True
errors_list.append((file_path, e))
finally:
if error:
timestamp = datetime.today().strftime("%Y-%m-%d_%H_%M_%S")
base_path, ext = os.path.splitext(file_path)
os.rename(file_path, base_path + "_" + timestamp + ext)
if errors_list:
print(errors_list, file=sys.stderr)
return errors_list
def get_project_info(self) -> ProjectInfoBase:
"""Get all information needed to save project"""
raise NotImplementedError
def set_project_info(self, data: ProjectInfoBase):
"""Set project info"""
raise NotImplementedError
@staticmethod
def verify_image(image: Image, silent=True) -> Union[Image, bool]:
if image.is_time:
if image.is_stack:
raise TimeAndStackException()
if silent:
return image.swap_time_and_stack()
else:
raise SwapTimeStackException()
return True
def change_profile(self, name):
self.current_profile_dict = name
if self.current_profile_dict not in self.view_settings_dict:
self.view_settings_dict = {
self.current_profile_dict: ProfileDict()
}
class ViewSettings(ImageSettings):
colormap_changes = Signal()
labels_changed = Signal()
theme_changed = Signal()
def __init__(self):
super().__init__()
self.color_map = []
self.border_val = []
self.current_profile_dict = "default"
self.view_settings_dict = ProfileDict()
self.colormap_dict = ColormapDict(
self.get_from_profile("custom_colormap", {}))
self.label_color_dict = LabelColorDict(
self.get_from_profile("custom_label_colors", {}))
self.cached_labels: Optional[Tuple[str, np.ndarray]] = None
@property
def theme_name(self) -> str:
return self.get_from_profile("theme", "light")
@property
def style_sheet(self):
palette = napari.utils.theme.palettes[self.theme_name]
palette["canvas"] = "black"
return napari_template(get_stylesheet(), **palette)
@theme_name.setter
def theme_name(self, value: str):
if value not in napari.utils.theme.palettes:
raise ValueError(
f"Unsupported theme {value}. Supported one: {self.theme_list()}"
)
if value == self.theme_name:
return
self.set_in_profile("theme", value)
self.theme_changed.emit()
@staticmethod
def theme_list():
return list(napari.utils.theme.palettes.keys())
@property
def chosen_colormap(self):
data = self.get_from_profile("colormaps", starting_colors[:])
res = [x for x in data if x in self.colormap_dict]
if len(res) != data:
if len(res) == 0:
res = starting_colors[:]
self.set_in_profile("colormaps", res)
return res
@chosen_colormap.setter
def chosen_colormap(self, val):
self.set_in_profile("colormaps", val)
self.colormap_changes.emit()
@property
def current_labels(self):
return self.get_from_profile("labels_used", "default")
@current_labels.setter
def current_labels(self, val):
if val not in self.label_color_dict:
raise ValueError(f"Unknown label scheme name '{val}'")
self.set_in_profile("labels_used", val)
self.labels_changed.emit()
@property
def label_colors(self):
key = self.current_labels
if key not in self.label_color_dict:
key = "default"
if not (self.cached_labels and key == self.cached_labels[0]):
self.cached_labels = key, self.label_color_dict.get_array(key)
return self.cached_labels[1]
def chosen_colormap_change(self, name, visibility):
colormaps = set(self.chosen_colormap)
if visibility:
colormaps.add(name)
else:
try:
colormaps.remove(name)
except KeyError:
pass
# TODO update sorting rule
self.chosen_colormap = list(
sorted(colormaps, key=self.colormap_dict.get_position))
def get_channel_info(self,
view: str,
num: int,
default: Optional[str] = None) -> List[str]:
cm = self.chosen_colormap
if default is None:
default = cm[num % len(cm)]
resp = self.get_from_profile(f"{view}.cmap{num}", default)
if resp not in self.colormap_dict:
resp = cm[num % len(cm)]
self.set_in_profile(f"{view}.cmap{num}", resp)
return resp
def set_channel_info(self, view: str, num, value: str):
self.set_in_profile(f"{view}.cmap{num}", value)
@property
def available_colormaps(self):
return list(self.colormap_dict.keys())
def _image_changed(self):
self.border_val = self.image.get_ranges()
super()._image_changed()
def change_profile(self, name):
self.current_profile_dict = name
if self.current_profile_dict not in self.view_settings_dict:
self.view_settings_dict = {
self.current_profile_dict: ProfileDict()
}
def set_in_profile(self, key_path, value):
"""
Function for saving information used in visualization. This is accessor to
:py:meth:`~.ProfileDict.set` of inner variable.
:param key_path: dot separated path
:param value: value to store. The value need to be json serializable. """
self.view_settings_dict.set(f"{self.current_profile_dict}.{key_path}",
value)
def get_from_profile(self, key_path, default=None):
"""
Function for getting information used in visualization. This is accessor to
:py:meth:`~.ProfileDict.get` of inner variable.
:param key_path: dot separated path
:param default: default value if key is missed
"""
return self.view_settings_dict.get(
f"{self.current_profile_dict}.{key_path}", default)
def dump_view_profiles(self):
# return json.dumps(self.profile_dict, cls=ProfileEncoder)
return self.view_settings_dict