feat: implement segmenter validation step in GUI

CHANGELOG

@@ -1,5 +1,5 @@
 0.6.0
- - feat: implement segmenter validation step in CLI
+ - feat: implement segmenter validation step in CLI and GUI
  - feat: support PyTorch segmentation models
  - fix: show correct default mask postprocessing arguments in CLI help
  - setup: bump dcnum from 0.22.1 to 0.23.2

chipstream/gui/manager.py

@@ -222,6 +222,9 @@ def run_job(self, path_in, path_out):
                                        path_out=path_out,
                                        **self.job_kwargs)
         self.jobs.append(job)
+        # Make sure the job will run (This must be done after adding it
+        # to the jobs list and before adding it to the runners list)
+        job.validate()
         with dclogic.DCNumJobRunner(job) as runner:
             self.runners.append(runner)
             # We might encounter a scenario in which the output file

tests/test_gui.py

@@ -122,6 +122,48 @@ def test_gui_segm_torch_model(mw, qtbot, monkeypatch):
                == f"torchmpo:m={path_model.name}:cle=1^f=1^clo=0"
 
 
+def test_gui_segm_torch_model_with_wrong_model(mw, qtbot, monkeypatch):
+    # Create a test dataset with metadata that will make the model invalid
+    path = retrieve_data(
+        "fmt-hdf5_cytoshot_full-features_legacy_allev_2023.zip")
+
+    with h5py.File(path, "a") as h5:
+        h5.attrs["setup:chip region"] = "reservoir"
+
+    path_model = retrieve_model(
+        "segm-torch-model_unet-dcnum-test_g1_910c2.zip")
+
+    # Import the model
+    monkeypatch.setattr(QtWidgets.QFileDialog, "getOpenFileNames",
+                        lambda *args: ([path_model], ""))
+    qtbot.mouseClick(mw.toolButton_torch_add, QtCore.Qt.MouseButton.LeftButton)
+    # select the model
+    for idm in range(mw.comboBox_torch_model.count()):
+        data = mw.comboBox_torch_model.itemData(idm)
+        if data.name == path_model.name:
+            break
+    else:
+        assert False
+
+    mw.comboBox_torch_model.setCurrentIndex(idm)
+
+    # Add the input file
+    mw.append_paths([path])
+
+    # Run the analysis
+    mw.on_run()
+    while mw.job_manager.is_busy():
+        time.sleep(.1)
+    out_path = path.with_name(path.stem + "_dcn.rtdc")
+    assert not out_path.exists()
+
+    # Make sure there is an error message in the interface
+    qtbot.mouseClick(mw.tableWidget_input.cellWidget(0, 2),
+                     QtCore.Qt.MouseButton.LeftButton)
+    assert mw.textBrowser.toPlainText().count(
+        "only experiments in channel region supported")
+
+
 def test_gui_set_pixel_size(mw):
     path = retrieve_data(
         "fmt-hdf5_cytoshot_full-features_legacy_allev_2023.zip")

tests/test_gui_manager.py

@@ -4,8 +4,9 @@
 
 from chipstream.gui import manager
 
+import h5py
 
-from helper_methods import retrieve_data
+from helper_methods import retrieve_data, retrieve_model
 
 
 def test_manager_get_paths_out(tmp_path):
@@ -90,6 +91,35 @@ def test_manager_run_defaults():
                                      "norm:o=0^s=10")
 
 
+def test_manager_run_error_wrong_model():
+    model_file = retrieve_model(
+        "segm-torch-model_unet-dcnum-test_g1_910c2.zip")
+
+    # Create a test dataset with metadata that will make the model invalid
+    path = retrieve_data(
+        "fmt-hdf5_cytoshot_full-features_legacy_allev_2023.zip")
+
+    with h5py.File(path, "a") as h5:
+        h5.attrs["setup:chip region"] = "reservoir"
+
+    mg = manager.ChipStreamJobManager()
+    mg.add_path(path)
+    mg.run_all_in_thread(job_kwargs={
+        "segmenter_code": "torchmpo",
+        "segmenter_kwargs": {"model_file": model_file}
+        }
+    )
+    # wait for the thread to join
+    mg.join()
+
+    assert mg.current_index == 0
+    assert mg[0]["progress"] == 0
+    assert mg[0]["state"] == "error"
+    assert mg.get_info(0).count("only experiments in channel region supported")
+
+    assert not mg.is_busy()
+
+
 def test_manager_run_with_path_out(tmp_path):
     path = retrieve_data(
         "fmt-hdf5_cytoshot_full-features_legacy_allev_2023.zip")