Describe the bug
save_movie function does not seem to interpret arguments. For instance, with the time_viewer argument set to True, the saved movie does not have a visible time viewer. The time_dilatation argument does not seem to have any impact either. Etc.
Steps to reproduce
Run the sEEG tutorial and uncomment the following line:
brain.save_movie(time_dilation=3, interpolation='linear', framerate=10,
time_viewer=True, filename='./mne-test-seeg.m4')
Expected results
I would expect the arguments to work. Especially time_dilatation, because right now for me it takes forever to save the movie.
Actual results
Resulting movie is 1 min 40 sec without time courses, unlike what is shown on the sEEG tutorial webpage.
Additional information
Platform: Linux-5.4.0-72-generic-x86_64-with-glibc2.31
Python: 3.9.2 | packaged by conda-forge | (default, Feb 21 2021, 05:02:46) [GCC 9.3.0]
Executable: ~/anaconda3/envs/neo_mne/bin/python
CPU: x86_64: 24 cores
Memory: 250.2 GB
mne: 0.23.0
numpy: 1.19.2 {blas=openblas, lapack=openblas}
scipy: 1.5.3
matplotlib: 3.3.4 {backend=Qt5Agg}
sklearn: 0.23.2
numba: 0.53.1
nibabel: 3.2.1
nilearn: 0.7.1
dipy: 1.2.0
cupy: Not found
pandas: 1.2.4
mayavi: 4.7.2
pyvista: 0.29.1 {pyvistaqt=0.3.0, OpenGL 4.5.0 NVIDIA 390.143 via Quadro P5000/PCIe/SSE2}
vtk: 9.0.1
PyQt5: 5.12.3
Describe the bug
save_movie function does not seem to interpret arguments. For instance, with the time_viewer argument set to True, the saved movie does not have a visible time viewer. The time_dilatation argument does not seem to have any impact either. Etc.
Steps to reproduce
Run the sEEG tutorial and uncomment the following line:
Expected results
I would expect the arguments to work. Especially time_dilatation, because right now for me it takes forever to save the movie.
Actual results
Resulting movie is 1 min 40 sec without time courses, unlike what is shown on the sEEG tutorial webpage.
Additional information
Platform: Linux-5.4.0-72-generic-x86_64-with-glibc2.31
Python: 3.9.2 | packaged by conda-forge | (default, Feb 21 2021, 05:02:46) [GCC 9.3.0]
Executable: ~/anaconda3/envs/neo_mne/bin/python
CPU: x86_64: 24 cores
Memory: 250.2 GB
mne: 0.23.0
numpy: 1.19.2 {blas=openblas, lapack=openblas}
scipy: 1.5.3
matplotlib: 3.3.4 {backend=Qt5Agg}
sklearn: 0.23.2
numba: 0.53.1
nibabel: 3.2.1
nilearn: 0.7.1
dipy: 1.2.0
cupy: Not found
pandas: 1.2.4
mayavi: 4.7.2
pyvista: 0.29.1 {pyvistaqt=0.3.0, OpenGL 4.5.0 NVIDIA 390.143 via Quadro P5000/PCIe/SSE2}
vtk: 9.0.1
PyQt5: 5.12.3