Fix pop_select dialog crash on numpy chanlocs

src/eegprep/functions/popfunc/pop_rejcont.py

@@ -8,6 +8,7 @@
 
 from eegprep.functions.guifunc.inputgui import inputgui
 from eegprep.functions.guifunc.spec import ControlSpec, DialogSpec
+from eegprep.functions.popfunc._chanutils import chanlocs_as_list
 from eegprep.functions.popfunc._pop_utils import format_history_value, parse_key_value_args
 from eegprep.functions.popfunc._rejection import copy_eeg, one_based_indices, parse_numeric_sequence
 from eegprep.functions.popfunc.pop_select import pop_select
@@ -245,7 +246,7 @@ def _rejcont_winrej(selected: np.ndarray, channel_count: int) -> np.ndarray:
 
 
 def _selected_chanlocs(EEG: dict[str, Any], selected_rows: np.ndarray) -> list[dict[str, Any]]:
-    chanlocs = list(EEG.get("chanlocs", []) or [])
+    chanlocs = chanlocs_as_list(EEG.get("chanlocs"))
     return [chanlocs[index] for index in selected_rows if index < len(chanlocs)]
 
 

src/eegprep/functions/popfunc/pop_rmbase.py

@@ -11,6 +11,7 @@
 from eegprep.functions.guifunc.inputgui import inputgui
 from eegprep.functions.guifunc.spec import CallbackSpec, ControlSpec, DialogSpec
 from eegprep.functions.miscfunc.misc import round_mat
+from eegprep.functions.popfunc._chanutils import chanlocs_as_list
 from eegprep.functions.popfunc._pop_utils import format_history_value, parse_text_tokens
 from eegprep.functions.popfunc.eeg_findboundaries import eeg_findboundaries
 from eegprep.functions.sigprocfunc.rmbase import rmbase
@@ -418,10 +419,7 @@ def _channel_field_values(EEG: dict[str, Any], field: str, *, unique: bool = Fal
 
 
 def _chanlocs(EEG: dict[str, Any]) -> list[dict[str, Any]]:
-    chanlocs = EEG.get("chanlocs", [])
-    if isinstance(chanlocs, np.ndarray):
-        chanlocs = chanlocs.tolist()
-    return [chan if isinstance(chan, dict) else {} for chan in list(chanlocs or [])]
+    return [chan if isinstance(chan, dict) else {} for chan in chanlocs_as_list(EEG.get("chanlocs"))]
 
 
 def _default_baseline_timerange(EEG: dict[str, Any]) -> str:

src/eegprep/functions/popfunc/pop_select.py

@@ -8,6 +8,7 @@
 from eegprep.functions.adminfunc.eeg_checkset import eeg_checkset
 from eegprep.functions.guifunc.inputgui import inputgui
 from eegprep.functions.guifunc.spec import CallbackSpec, ControlSpec, DialogSpec
+from eegprep.functions.popfunc._chanutils import chanlocs_as_list
 from eegprep.functions.popfunc._pop_utils import (
     format_history_value,
     parse_key_value_args,
@@ -578,7 +579,9 @@ def _clip_time_matrix(mat):
 
 def pop_select_dialog_spec(EEG) -> DialogSpec:
     """Return the EEGLAB-like dialog spec for ``pop_select``."""
-    chanlocs = list(EEG.get("chanlocs", []) or [])
+    # eeg_checkset stores EEG['chanlocs'] as a numpy object array, so use the
+    # shared helper instead of `or []`, which raises on ndarray truth checks.
+    chanlocs = chanlocs_as_list(EEG.get("chanlocs"))
     channel_labels = tuple(str(chan.get("labels", "")) for chan in chanlocs if isinstance(chan, dict))
     channel_types = tuple(
         value

src/eegprep/plugins/ICLabel/_prop_numerics.py

@@ -17,6 +17,7 @@
     numeric_vector,
     parse_plot_options_text,
 )
+from eegprep.functions.popfunc._chanutils import chanlocs_as_list
 from eegprep.functions.popfunc._rejection import component_rejection_flags, one_based_indices
 from eegprep.functions.sigprocfunc.spectopo import compute_spectra
 from eegprep.plugins.dipfit._utils import normalize_model_list
@@ -263,7 +264,7 @@ def _channel_dashboard_data(
         figure_title=f"Channel {label} - pop_prop_extended()",
         topography_title=f"Channel {label}",
         topography_values=index,
-        topography_chanlocs=list(EEG.get("chanlocs", []) or []),
+        topography_chanlocs=chanlocs_as_list(EEG.get("chanlocs")),
         activity=activity,
         times_ms=times_ms,
         activity_title="Channel Time Series",

src/eegprep/plugins/clean_rawdata/vis_artifacts.py

@@ -7,6 +7,7 @@
 
 import numpy as np
 
+from eegprep.functions.popfunc._chanutils import chanlocs_as_list
 from eegprep.functions.sigprocfunc.eegplot import eegplot
 from eegprep.plugins.clean_rawdata.private.masks import mask_to_intervals
 
@@ -142,9 +143,4 @@ def _nbchan(eeg: dict[str, Any]) -> int:
 
 
 def _chanlocs(eeg: dict[str, Any]) -> list[dict[str, Any]]:
-    chanlocs = eeg.get("chanlocs", [])
-    if isinstance(chanlocs, np.ndarray):
-        chanlocs = chanlocs.tolist()
-    if isinstance(chanlocs, dict):
-        chanlocs = [chanlocs]
-    return [chan if isinstance(chan, dict) else {} for chan in list(chanlocs or [])]
+    return [chan if isinstance(chan, dict) else {} for chan in chanlocs_as_list(eeg.get("chanlocs"))]

src/eegprep/plugins/firfilt/_filtering.py

@@ -9,6 +9,7 @@
 from scipy.signal import filtfilt, firls, firwin, lfilter, minimum_phase, remez
 from scipy.signal import windows as signal_windows
 
+from eegprep.functions.popfunc._chanutils import chanlocs_as_list
 from eegprep.plugins.firfilt.findboundaries import findboundaries
 from eegprep.plugins.firfilt.fir_filterdcpadded import fir_filterdcpadded
 from eegprep.plugins.firfilt.firws import firws
@@ -475,7 +476,4 @@ def _has_values(value: Any) -> bool:
 
 
 def _chanlocs(EEG: dict[str, Any]) -> list[dict[str, Any]]:
-    chanlocs = EEG.get("chanlocs", [])
-    if isinstance(chanlocs, np.ndarray):
-        chanlocs = chanlocs.tolist()
-    return [chan if isinstance(chan, dict) else {} for chan in list(chanlocs or [])]
+    return [chan if isinstance(chan, dict) else {} for chan in chanlocs_as_list(EEG.get("chanlocs"))]

src/eegprep/plugins/firfilt/_pop_common.py

@@ -7,6 +7,7 @@
 import numpy as np
 
 from eegprep.functions.guifunc.spec import CallbackSpec, ControlSpec
+from eegprep.functions.popfunc._chanutils import chanlocs_as_list
 from eegprep.functions.popfunc._pop_utils import format_history_value, parse_key_value_args
 
 
@@ -168,7 +169,4 @@ def _channel_field_values(EEG: dict[str, Any], field: str, *, unique: bool = Fal
 
 
 def _chanlocs(EEG: dict[str, Any]) -> list[dict[str, Any]]:
-    chanlocs = EEG.get("chanlocs", [])
-    if isinstance(chanlocs, np.ndarray):
-        chanlocs = chanlocs.tolist()
-    return [chan if isinstance(chan, dict) else {} for chan in list(chanlocs or [])]
+    return [chan if isinstance(chan, dict) else {} for chan in chanlocs_as_list(EEG.get("chanlocs"))]

tests/test_gui_pop_clean_rawdata.py

@@ -160,6 +160,7 @@ def run(self, spec, initial_values=None):
 
     def test_vis_artifacts_diagnostics_summarizes_samples_and_channels(self):
         old = _eeg()
+        old["chanlocs"] = np.asarray(old["chanlocs"], dtype=object)
         new = dict(
             old,
             data=old["data"][:, :30],

tests/test_gui_pop_firfilt.py

@@ -54,6 +54,15 @@ def test_pop_eegfiltnew_dialog_matches_eeglab_sections(self):
         self.assertIn(("text", "Channel type(s)", None), labels)
         self.assertIn(("text", "OR channel labels or indices", None), labels)
 
+    def test_pop_eegfiltnew_dialog_accepts_numpy_chanlocs(self):
+        eeg = _eeg()
+        eeg["chanlocs"] = np.asarray(eeg["chanlocs"], dtype=object)
+
+        controls = controls_by_tag(pop_eegfiltnew_dialog_spec(eeg))
+
+        self.assertEqual(controls["chantype_button"].callback.params["channels"], ["EEG", "EOG"])
+        self.assertEqual(controls["channels_button"].callback.params["channels"], ["Cz", "Pz", "EOG"])
+
     def test_pop_eegfiltnew_gui_result_filters_and_returns_history(self):
         class Renderer:
             def run(self, spec, initial_values=None):
@@ -100,6 +109,26 @@ def run(self, spec, initial_values=None):
         np.testing.assert_allclose(out["data"][2], before[2])
         self.assertIn("'channels', {'Cz' 'Pz'}", command)
 
+    def test_pop_eegfiltnew_accepts_numpy_chanlocs_for_channel_type_filtering(self):
+        eeg = _eeg()
+        eeg["chanlocs"] = np.asarray(eeg["chanlocs"], dtype=object)
+        before = eeg["data"].copy()
+
+        out, command = pop_eegfiltnew(
+            eeg,
+            "hicutoff",
+            30,
+            "filtorder",
+            80,
+            "chantype",
+            ["EOG"],
+            return_com=True,
+        )
+
+        np.testing.assert_allclose(out["data"][:2], before[:2])
+        self.assertFalse(np.allclose(out["data"][2], before[2]))
+        self.assertIn("'chantype', {'EOG'}", command)
+
     def test_legacy_pop_eegfilt_dialog_and_gui_result(self):
         spec = pop_eegfilt_dialog_spec(_eeg())
 

tests/test_gui_pop_select.py

@@ -85,6 +85,17 @@ def test_gui_channel_picker_exposes_labels_and_types(self):
         self.assertEqual(controls["chans_button"].callback.params["channels"], ("Fz", "Cz", "HEOG", "VEOG"))
         self.assertEqual(controls["chantype_button"].callback.params["channels"], ("EEG", "EOG"))
 
+    def test_gui_dialog_spec_accepts_numpy_chanlocs(self):
+        # eeg_checkset normalises EEG['chanlocs'] to a numpy array of dicts;
+        # the dialog builder must accept that storage form (regression for #229).
+        eeg = _eeg()
+        eeg["chanlocs"] = np.asarray(eeg["chanlocs"], dtype=object)
+
+        controls = controls_by_tag(pop_select_dialog_spec(eeg))
+
+        self.assertEqual(controls["chans_button"].callback.params["channels"], ("Fz", "Cz", "HEOG", "VEOG"))
+        self.assertEqual(controls["chantype_button"].callback.params["channels"], ("EEG", "EOG"))
+
     def test_gui_result_runs_selection_and_history(self):
         class Renderer:
             def run(self, spec, initial_values=None):

tests/test_pop_prop_extended.py

@@ -73,6 +73,16 @@ def test_classifier_data_parsing_defaults_to_iclabel_and_standard_classes() -> N
     assert classifier_names(eeg) == ["Other", "ICLabel"]
 
 
+def test_channel_property_data_accepts_numpy_chanlocs() -> None:
+    eeg = _iclabel_eeg()
+    eeg["chanlocs"] = np.asarray(eeg["chanlocs"], dtype=object)
+
+    dashboard = build_extended_property_data(eeg, 1, 1)
+
+    assert len(dashboard.topography_chanlocs) == 4
+    assert dashboard.topography_chanlocs[0]["labels"] == "Ch1"
+
+
 def test_classifier_name_from_gui_matches_string_values_case_insensitively() -> None:
     eeg = _iclabel_eeg()
 

tests/test_pop_rmbase.py

@@ -227,6 +227,23 @@ def test_pop_rmbase_dialog_disables_channel_controls_for_multiple_datasets():
     assert controls["channels_button"].enabled is False
 
 
+def test_pop_rmbase_dialog_accepts_numpy_chanlocs():
+    eeg = create_test_eeg(n_channels=2, n_samples=50, srate=50.0, n_trials=2)
+    eeg["chanlocs"] = np.asarray(
+        [
+            {"labels": "Cz", "type": "EEG"},
+            {"labels": "EOG", "type": "EOG"},
+        ],
+        dtype=object,
+    )
+
+    spec = pop_rmbase_dialog_spec(eeg)
+    controls = {control.tag: control for control in spec.controls if control.tag}
+
+    assert controls["chantypes_button"].callback.params["channels"] == ["EEG", "EOG"]
+    assert controls["channels_button"].callback.params["channels"] == ["Cz", "EOG"]
+
+
 def test_pop_rmbase_sample_data_zeroes_selected_baseline_channels_without_warnings():
     eeg = pop_loadset(SAMPLE_DATASET_PATH)
 

tests/test_rejection_workflows.py

@@ -308,12 +308,14 @@ def fake_eegplot(_data, *args, **kwargs):
 def test_pop_rejcont_display_accept_removes_continuous_regions(monkeypatch):
     accepted = []
     eeg = create_test_eeg(n_channels=2, n_samples=120, n_trials=1, srate=100)
+    eeg["chanlocs"] = np.asarray(eeg["chanlocs"], dtype=object)
     time = np.arange(120) / 100
     eeg["data"][0] = 100 * np.sin(2 * np.pi * 30 * time)
 
     def fake_eegplot(data, *args, **kwargs):
         del args
         assert np.asarray(data).shape[0] == 1
+        assert kwargs["eloc_file"][0]["labels"] == "Ch1"
         kwargs["command_callback"](kwargs["winrej"])
         return "window"