- transforms bugfixes

ndbioimage/__init__.py

@@ -40,6 +40,7 @@ except (Exception,):
 
 ureg.default_format = '~P'
 set_application_registry(ureg)
+warnings.filterwarnings('ignore', 'Reference to unknown ID')
 
 
 class ReaderNotFoundError(Exception):
@@ -51,7 +52,7 @@ class ImTransforms(Transforms):
 
     def __init__(self, path, cyllens, file=None, transforms=None):
         super().__init__()
-        self.cyllens = cyllens
+        self.cyllens = tuple(cyllens)
         if transforms is None:
             # TODO: check this
             if re.search(r'^Pos\d+', path.name):
@@ -106,7 +107,7 @@ class ImTransforms(Transforms):
                 files = (Path(files),)
             elif isinstance(files, Path):
                 files = (files,)
-            return files
+            return tuple(files)
         except (Exception,):
             return ()
 
@@ -1375,6 +1376,13 @@ class AbstractReader(Imread, metaclass=ABCMeta):
         else:
             self.immersionN = 1
 
+        p = re.compile(r'(\d+):(\d+)$')
+        try:
+            self.track, self.detector = zip(*[[int(i) for i in p.findall(find(
+                self.ome.images[0].pixels.channels, id=f'Channel:{c}').detector_settings.id)[0]]
+                                              for c in range(self.shape['c'])])
+        except Exception:
+            pass
 
 def main():
     parser = ArgumentParser(description='Display info and save as tif')

ndbioimage/readers/cziread.py

@@ -182,7 +182,7 @@ class Reader(AbstractReader, ABC):
 
             ome.images[0].pixels.channels.append(
                 model.Channel(
-                    id=f"Channel:0:{idx}",
+                    id=f"Channel:{idx}",
                     name=channel.attrib["Name"],
                     acquisition_mode=text(channel.find("AcquisitionMode")),
                     color=model.Color(text(channels_ds[channel.attrib["Id"]].find("Color"))),
@@ -378,12 +378,12 @@ class Reader(AbstractReader, ABC):
 
             ome.images[0].pixels.channels.append(
                 model.Channel(
-                    id=f"Channel:0:{idx}",
+                    id=f"Channel:{idx}",
                     name=channel.attrib["Name"],
                     acquisition_mode=text(channel.find("AcquisitionMode")),
                     color=model.Color(text(channels_ds[channel.attrib["Id"]].find("Color"))),
                     detector_settings=model.DetectorSettings(id=detector.attrib["Id"], binning=binning),
-                    emission_wavelength=text(channel.find("EmissionWavelength")),
+                    # emission_wavelength=text(channel.find("EmissionWavelength")),  # TODO: fix
                     excitation_wavelength=light_source_settings.wavelength,
                     filter_set_ref=model.FilterSetRef(id=ome.instruments[0].filter_sets[filterset_idx].id),
                     illumination_type=text(channel.find("IlluminationType")),

ndbioimage/readers/seqread.py

@@ -15,7 +15,7 @@ def lazy_property(function, field, *arg_fields):
     def lazy(self):
         if self.__dict__.get(field) is None:
             self.__dict__[field] = function(*[getattr(self, arg_field) for arg_field in arg_fields])
-            self.__fields_set__.add(field)
+            self.model_fields_set.add(field)
         return self.__dict__[field]
     return property(lazy)
 

ndbioimage/transforms.py

@@ -66,6 +66,9 @@ class Transforms(dict):
     def __setstate__(self, state):
         self.__dict__.update(state)
 
+    def __hash__(self):
+        return hash(frozenset((*self.__dict__.items(), *self.items())))
+
     def save(self, file):
         with open(file.with_suffix(".yml"), 'w') as f:
             yaml.safe_dump(self.asdict(), f, default_flow_style=None)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "ndbioimage"
-version = "2023.9.0"
+version = "2023.10.0"
 description = "Bio image reading, metadata and some affine registration."
 authors = ["W. Pomp <w.pomp@nki.nl>"]
 license = "GPLv3"