Merge pull request #167 from MannLabs/fix_165

fix some small bugs

src/scportrait/pipeline/featurization.py

@@ -1161,7 +1161,7 @@ def _generate_column_names(
         column_names = []
 
         if n_masks == 1:
-            self.project._check_sdata_status()
+            self.project.get_project_status()
 
             if self.project.nuc_seg_status:
                 mask_name = self.MASK_NAMES[0]

src/scportrait/pipeline/project.py

@@ -1125,7 +1125,7 @@ def featurize(
 
         # check that prerequisits are fullfilled to featurize cells
         assert self.featurization_f is not None, "No featurization method defined."
-        assert not (
+        assert (
             self.nuc_seg_status or self.cyto_seg_status
         ), "No nucleus or cytosol segmentation loaded. Please load a segmentation first."
         assert self.extraction_status, "No single cell data extracted. Please extract single cell data first."

src/scportrait/pipeline/segmentation/workflows.py

@@ -1477,15 +1477,15 @@ def cellpose_segmentation(self, input_image):
                 np.max(input_image) - np.min(input_image)
             )  # min max normalize to 0-1 range as cellpose expects this
 
-        masks, _, _, _ = model.eval(
+        masks = model.eval(
             [input_image],
             rescale=self.rescale,
             normalize=self.normalize,
             diameter=self.diameter,
             flow_threshold=self.flow_threshold,
             cellprob_threshold=self.cellprob_threshold,
             channels=[1, 0],
-        )
+        )[0]
         masks = np.array(masks)  # convert to array
 
         # ensure all edge classes are removed
@@ -1587,15 +1587,15 @@ def cellpose_segmentation(self, input_image):
                 np.max(input_image) - np.min(input_image)
             )  # min max normalize to 0-1 range as cellpose expects this
 
-        masks_nucleus, _, _, _ = model.eval(
+        masks_nucleus = model.eval(
             [input_image],
             rescale=self.rescale,
             normalize=self.normalize,
             diameter=self.diameter,
             flow_threshold=self.flow_threshold,
             cellprob_threshold=self.cellprob_threshold,
             channels=[1, 0],
-        )
+        )[0]
         masks_nucleus = np.array(masks_nucleus)  # convert to array
 
         # manually delete model and perform gc to free up memory on GPU
@@ -1610,15 +1610,15 @@ def cellpose_segmentation(self, input_image):
 
         model = self._load_model(model_type="cytosol", gpu=self.use_GPU, device=self.device)
 
-        masks_cytosol, _, _, _ = model.eval(
+        masks_cytosol = model.eval(
             [input_image],
             rescale=self.rescale,
             normalize=self.normalize,
             diameter=self.diameter,
             flow_threshold=self.flow_threshold,
             cellprob_threshold=self.cellprob_threshold,
             channels=[2, 1],
-        )
+        )[0]
         masks_cytosol = np.array(masks_cytosol)  # convert to array
 
         # manually delete model and perform gc to free up memory on GPU
@@ -1852,15 +1852,15 @@ def cellpose_segmentation(self, input_image):
                 np.max(input_image) - np.min(input_image)
             )  # min max normalize to 0-1 range as cellpose expects this
 
-        masks_cytosol, _, _, _ = model.eval(
+        masks_cytosol = model.eval(
             [input_image],
             rescale=self.rescale,
             normalize=self.normalize,
             diameter=self.diameter,
             flow_threshold=self.flow_threshold,
             cellprob_threshold=self.cellprob_threshold,
             channels=[2, 1],
-        )
+        )[0]
         masks_cytosol = np.array(masks_cytosol)  # convert to array
 
         # manually delete model and perform gc to free up memory on GPU

src/scportrait/pipeline/selection.py

@@ -84,6 +84,8 @@ def _setup_selection(self):
             except KeyError:
                 Warning("No name provided for the selection. Will use default name.")
                 name = "selected_cells"
+        else:
+            name = self.name
 
         # create savepath
         savename = name.replace(" ", "_") + ".xml"