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# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
import os
from contextlib import nullcontext
from pathlib import Path
import numpy as np
import pytest
from numpy.testing import assert_allclose
import mne
from mne._fiff.constants import FIFF
from mne.channels import DigMontage
from mne.coreg import Coregistration
from mne.datasets import testing
from mne.io import read_info
from mne.utils import catch_logging, get_config
from mne.viz import _3d
data_path = testing.data_path(download=False)
raw_path = data_path / "MEG" / "sample" / "sample_audvis_trunc_raw.fif"
fname_trans = data_path / "MEG" / "sample" / "sample_audvis_trunc-trans.fif"
subjects_dir = data_path / "subjects"
fid_fname = subjects_dir / "sample" / "bem" / "sample-fiducials.fif"
ctf_raw_path = data_path / "CTF" / "catch-alp-good-f.ds"
nirx_15_0_raw_path = (
data_path / "NIRx" / "nirscout" / "nirx_15_0_recording" / "NIRS-2019-10-27_003.hdr"
)
nirsport2_raw_path = (
data_path / "NIRx" / "nirsport_v2" / "aurora_2021_9" / "2021-10-01_002_config.hdr"
)
snirf_nirsport2_raw_path = (
data_path / "SNIRF" / "NIRx" / "NIRSport2" / "1.0.3" / "2021-05-05_001.snirf"
)
pytest.importorskip("nibabel")
class TstVTKPicker:
"""Class to test cell picking."""
def __init__(self, mesh, cell_id, event_pos):
self.mesh = mesh
self.cell_id = cell_id
self.point_id = None
self.event_pos = event_pos
def GetCellId(self):
"""Return the picked cell."""
return self.cell_id
def GetDataSet(self):
"""Return the picked mesh."""
return self.mesh
def GetPickPosition(self):
"""Return the picked position."""
vtk_cell = self.mesh.GetCell(self.cell_id)
cell = [
vtk_cell.GetPointId(point_id)
for point_id in range(vtk_cell.GetNumberOfPoints())
]
self.point_id = cell[0]
return self.mesh.points[self.point_id]
def GetEventPosition(self):
"""Return event position."""
return self.event_pos
@pytest.mark.slowtest
@testing.requires_testing_data
@pytest.mark.parametrize(
"inst_path",
(
raw_path,
"gen_montage",
ctf_raw_path,
nirx_15_0_raw_path,
nirsport2_raw_path,
snirf_nirsport2_raw_path,
),
)
def test_coreg_gui_pyvista_file_support(
inst_path, tmp_path, renderer_interactive_pyvistaqt
):
"""Test reading supported files."""
from mne.gui import coregistration
if inst_path == "gen_montage":
# generate a montage fig to use as inst.
tmp_info = read_info(raw_path)
eeg_chans = []
for pt in tmp_info["dig"]:
if pt["kind"] == FIFF.FIFFV_POINT_EEG:
eeg_chans.append(f"EEG {pt['ident']:03d}")
dig = DigMontage(dig=tmp_info["dig"], ch_names=eeg_chans)
inst_path = tmp_path / "tmp-dig.fif"
dig.save(inst_path)
if inst_path == ctf_raw_path:
ctx = pytest.warns(RuntimeWarning, match="MEG ref channel RMSP")
elif inst_path == snirf_nirsport2_raw_path: # TODO: This is maybe a bug?
ctx = pytest.warns(RuntimeWarning, match='assuming "head"')
else:
ctx = nullcontext()
with ctx:
coreg = coregistration(
inst=inst_path, subject="sample", subjects_dir=subjects_dir
)
coreg._accept_close_event = True
coreg.close()
@pytest.mark.slowtest
@testing.requires_testing_data
def test_coreg_gui_pyvista_basic(tmp_path, monkeypatch, renderer_interactive_pyvistaqt):
"""Test that using CoregistrationUI matches mne coreg."""
from mne.gui import coregistration
config = get_config()
# the sample subject in testing has MRI fids
assert (subjects_dir / "sample" / "bem" / "sample-fiducials.fif").is_file()
coreg = coregistration(
subject="sample", subjects_dir=subjects_dir, trans=fname_trans
)
assert coreg._lock_fids
coreg._reset_fiducials()
coreg.close()
# make it always log the distances
monkeypatch.setattr(_3d.logger, "info", _3d.logger.warning)
with catch_logging() as log:
coreg = coregistration(
inst=raw_path,
subject="sample",
head_high_res=False, # for speed
subjects_dir=subjects_dir,
verbose="debug",
)
log = log.getvalue()
assert "Total 16/78 points inside the surface" in log
coreg._set_fiducials_file(fid_fname)
assert coreg._fiducials_file == str(fid_fname)
# fitting (with scaling)
assert not coreg._mri_scale_modified
coreg._reset()
coreg._reset_fitting_parameters()
coreg._set_scale_mode("uniform")
coreg._fits_fiducials()
assert_allclose(
coreg.coreg._scale, np.array([97.46, 97.46, 97.46]) * 1e-2, atol=1e-3
)
shown_scale = [coreg._widgets[f"s{x}"].get_value() for x in "XYZ"]
assert_allclose(shown_scale, coreg.coreg._scale * 100, atol=1e-2)
coreg._set_icp_fid_match("nearest")
coreg._set_scale_mode("3-axis")
coreg._fits_icp()
assert_allclose(
coreg.coreg._scale, np.array([104.43, 101.47, 125.78]) * 1e-2, atol=1e-3
)
shown_scale = [coreg._widgets[f"s{x}"].get_value() for x in "XYZ"]
assert_allclose(shown_scale, coreg.coreg._scale * 100, atol=1e-2)
coreg._set_scale_mode("None")
coreg._set_icp_fid_match("matched")
assert coreg._mri_scale_modified
# unlock fiducials
assert coreg._lock_fids
coreg._set_lock_fids(False)
assert not coreg._lock_fids
# picking
assert not coreg._mri_fids_modified
vtk_picker = TstVTKPicker(coreg._surfaces["head"], 0, (0, 0))
coreg._on_mouse_move(vtk_picker, None)
coreg._on_button_press(vtk_picker, None)
coreg._on_pick(vtk_picker, None)
coreg._on_button_release(vtk_picker, None)
coreg._on_pick(vtk_picker, None) # also pick when locked
assert coreg._mri_fids_modified
# lock fiducials
coreg._set_lock_fids(True)
assert coreg._lock_fids
# fitting (no scaling)
assert coreg._nasion_weight == 10.0
coreg._set_point_weight(11.0, "nasion")
assert coreg._nasion_weight == 11.0
coreg._fit_fiducials()
with catch_logging() as log:
coreg._redraw() # actually emit the log
log = log.getvalue()
assert "Total 6/78 points inside the surface" in log
with catch_logging() as log:
coreg._fit_icp()
coreg._redraw()
log = log.getvalue()
assert "Total 38/78 points inside the surface" in log
assert coreg.coreg._extra_points_filter is None
coreg._omit_hsp()
with catch_logging() as log:
coreg._redraw()
log = log.getvalue()
assert "Total 29/53 points inside the surface" in log
assert coreg.coreg._extra_points_filter is not None
coreg._reset_omit_hsp_filter()
with catch_logging() as log:
coreg._redraw()
log = log.getvalue()
assert "Total 38/78 points inside the surface" in log
assert coreg.coreg._extra_points_filter is None
assert coreg._grow_hair == 0
coreg._fit_fiducials() # go back to few inside to start
with catch_logging() as log:
coreg._redraw()
log = log.getvalue()
assert "Total 6/78 points inside the surface" in log
norm = np.linalg.norm(coreg._head_geo["rr"]) # what's used for inside
assert_allclose(norm, 5.949288, atol=1e-3)
coreg._set_grow_hair(20.0)
with catch_logging() as log:
coreg._redraw()
assert coreg._grow_hair == 20.0
norm = np.linalg.norm(coreg._head_geo["rr"])
assert_allclose(norm, 6.555220, atol=1e-3) # outward
log = log.getvalue()
assert "Total 8/78 points inside the surface" in log # more outside now
# visualization
assert not coreg._helmet
assert coreg._actors["helmet"] is None
coreg._set_helmet(True)
assert coreg._eeg_channels
coreg._set_eeg_channels(False)
assert not coreg._eeg_channels
assert coreg._helmet
with catch_logging() as log:
coreg._redraw(verbose="debug")
log = log.getvalue()
assert "Drawing helmet" in log
coreg._set_point_weight(1.0, "nasion")
coreg._fit_fiducials()
with catch_logging() as log:
coreg._redraw(verbose="debug")
log = log.getvalue()
assert "Drawing helmet" in log
assert not coreg._meg_channels
assert coreg._actors["helmet"] is not None
# TODO: Someday test our file dialogs like:
# coreg._widgets["save_trans"].widget.click()
assert len(coreg._actors["sensors"]) == 0
coreg._set_meg_channels(True)
assert coreg._meg_channels
with catch_logging() as log:
coreg._redraw(verbose="debug")
assert "Drawing meg sensors" in log.getvalue()
assert coreg._actors["helmet"] is not None
assert len(coreg._actors["sensors"]) == 306
assert coreg._orient_glyphs
assert coreg._scale_by_distance
assert coreg._mark_inside
assert_allclose(
coreg._head_opacity, float(config.get("MNE_COREG_HEAD_OPACITY", "0.8"))
)
assert coreg._hpi_coils
assert coreg._head_shape_points
assert coreg._scale_mode == "None"
assert coreg._icp_fid_match == "matched"
assert coreg._head_resolution is False
assert coreg._trans_modified
tmp_trans = tmp_path / "tmp-trans.fif"
coreg._save_trans(tmp_trans)
assert not coreg._trans_modified
assert tmp_trans.is_file()
# first, disable auto cleanup
coreg._renderer._window_close_disconnect(after=True)
# test _close_callback()
coreg._renderer._process_events()
assert coreg._mri_fids_modified # should prompt
assert coreg._renderer.plotter.app_window.children() is not None
assert "close_dialog" not in coreg._widgets
assert not coreg._renderer.plotter._closed
assert coreg._accept_close_event
# make sure it's ignored (PySide6 causes problems here and doesn't wait)
coreg._accept_close_event = False
coreg.close()
assert not coreg._renderer.plotter._closed
coreg._widgets["close_dialog"].trigger("Discard") # do not save
coreg.close()
assert coreg._renderer.plotter._closed
coreg._clean() # finally, cleanup internal structures
assert coreg._renderer is None
# Coregistration instance should survive
assert isinstance(coreg.coreg, Coregistration)
@pytest.mark.slowtest
@testing.requires_testing_data
def test_fullscreen(renderer_interactive_pyvistaqt):
"""Test fullscreen mode."""
from mne.gui import coregistration
# Fullscreen mode
coreg = coregistration(subject="sample", subjects_dir=subjects_dir, fullscreen=True)
coreg._accept_close_event = True
coreg.close()
@pytest.mark.slowtest
@testing.requires_testing_data
def test_coreg_gui_scraper(tmp_path, renderer_interactive_pyvistaqt):
"""Test the scrapper for the coregistration GUI."""
pytest.importorskip("sphinx_gallery")
from mne.gui import coregistration
coreg = coregistration(
subject="sample", subjects_dir=subjects_dir, trans=fname_trans
)
(tmp_path / "_images").mkdir()
image_path = tmp_path / "_images" / "temp.png"
gallery_conf = dict(builder_name="html", src_dir=tmp_path)
block_vars = dict(
example_globals=dict(gui=coreg), image_path_iterator=iter([str(image_path)])
)
assert not image_path.is_file()
assert not getattr(coreg, "_scraped", False)
mne.gui._GUIScraper()(None, block_vars, gallery_conf)
assert image_path.is_file()
assert coreg._scraped
@pytest.mark.slowtest
@testing.requires_testing_data
def test_coreg_gui_notebook(renderer_notebook, nbexec):
"""Test the coregistration UI in a notebook."""
import pytest
import mne
from mne.datasets import testing
from mne.gui import coregistration
mne.viz.set_3d_backend("notebook") # set the 3d backend
with pytest.MonkeyPatch().context() as mp:
mp.delenv("_MNE_FAKE_HOME_DIR")
data_path = testing.data_path(download=False)
subjects_dir = data_path / "subjects"
coregistration(subject="sample", subjects_dir=subjects_dir)
@pytest.mark.slowtest
def test_no_sparse_head(subjects_dir_tmp, renderer_interactive_pyvistaqt, monkeypatch):
"""Test mne.gui.coregistration with no sparse head."""
from mne.gui import coregistration
subjects_dir_tmp = Path(subjects_dir_tmp)
subject = "sample"
out_rr, out_tris = mne.read_surface(
subjects_dir_tmp / subject / "bem" / "outer_skin.surf"
)
for head in ("sample-head.fif", "outer_skin.surf"):
os.remove(subjects_dir_tmp / subject / "bem" / head)
# Avoid actually doing the decimation (it's slow)
monkeypatch.setattr(
mne.coreg, "decimate_surface", lambda rr, tris, n_triangles: (out_rr, out_tris)
)
with pytest.warns(RuntimeWarning, match="No low-resolution head found"):
coreg = coregistration(
inst=raw_path, subject=subject, subjects_dir=subjects_dir_tmp
)
coreg.close()
def test_splash_closed(tmp_path, renderer_interactive_pyvistaqt):
"""Test that the splash closes on error."""
from mne.gui import coregistration
with pytest.raises(RuntimeError, match="No standard head model"):
coregistration(subjects_dir=tmp_path, subject="fsaverage")
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