Updates for TREC pipelines

Changes supporting use of pipelines in trec-adaptive-feedback project:

• generally, accessors' and models' IDs can be set with respective argument
• test client methods now handle response success check and variable parsing
• implemented functional threshold segmentation and (in base.roiset) classification models; threshold is relative to dataset full range (0.0 to 1.0)
• consequently, more tests cover base package without dependency on ilastik
• RoiSet returned by pipelines get IDs and are registered in server session, accesible at respective endpoints
• Pydantic models only used by FastAPI now; underlying model, accessor, and pipeline functions should interact with python objects and parameter dictionaries only
• RoiSet filters also include minimal and diagonal height, width dimension; are applied before time-intensity pixel array operations to increase performance
• performance improvement when passing patch stacks to ilastik pixel classifier
• RoiSet.classify_by can optionally filter by additional classification columns, e.g. to implement intensity gating

model_server/base/accessors.py

@@ -77,14 +77,14 @@ class GenericImageDataAccessor(ABC):
         return self.data.sum(axis=(0, 1, 2))
 
     @property
-    def data_xy(self) -> np.ndarray:
+    def data_yx(self) -> np.ndarray:
         if not self.chroma == 1 and self.nz == 1:
             raise InvalidDataShape('Can only return XY array from accessors with a single channel and single z-level')
         else:
             return self.data[:, :, 0, 0]
 
     @property
-    def data_xyz(self) -> np.ndarray:
+    def data_yxz(self) -> np.ndarray:
         if not self.chroma == 1:
             raise InvalidDataShape('Can only return XYZ array from accessors with a single channel')
         else:
@@ -428,6 +428,20 @@ class PatchStack(InMemoryDataAccessor):
     def count(self):
         return self.shape_dict['P']
 
+    @property
+    def data_yx(self) -> np.ndarray:
+        if not self.chroma == 1 and self.nz == 1:
+            raise InvalidDataShape('Can only return XY array from accessors with a single channel and single z-level')
+        else:
+            return self.data[:, :, :, 0, 0]
+
+    @property
+    def data_yxz(self) -> np.ndarray:
+        if not self.chroma == 1:
+            raise InvalidDataShape('Can only return XYZ array from accessors with a single channel')
+        else:
+            return self.data[:, :, :, 0, :]
+
     def export_pyxcz(self, fpath: Path):
         tzcyx = np.moveaxis(
             self.pyxcz,  # yxcz