[GUI] Additional PyQt5 dependency? #103
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|
Yes, we took the same approach as The difference with The error message should be improved, it's not super explicit, and maybe also let's add a note in the tutorial. Would that be acceptable to resolve this issue? |
sure. thanks for the delineation. :) |
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Describe the bug
Invoking the GUI after an installation of
mne-icalabel[gui]via pip on a Windows 11 and Debian bookworm machine in a fresh Python 3.9 environment fails with anInstalling PyQt5 resolves the error.
Steps to reproduce
On both machines, I performed the following installations:
and then followed the tutorial exactly. Here is the outcome
click to expand Windows CMD
click to expand Linux zsh
``` (joss) adina@muninn in ~/repos/mne-icalabel on git:main! ❱ ipython Python 3.9.12 (main, Mar 24 2022, 13:02:21) Type 'copyright', 'credits' or 'license' for more information IPython 8.4.0 -- An enhanced Interactive Python. Type '?' for help.In [1]: import os
...:
...: import mne
...: from mne.preprocessing import ICA
...:
...: from mne_icalabel.gui import label_ica_components
In [2]: sample_data_folder = mne.datasets.sample.data_path()
...: sample_data_raw_file = os.path.join(
...: sample_data_folder, "MEG", "sample", "sample_audvis_filt-0-40_raw.fif"
...: )
...: raw = mne.io.read_raw_fif(sample_data_raw_file)
...:
...: # Here we'll crop to 60 seconds and drop gradiometer channels for speed
...: raw.crop(tmax=60.0).pick_types(meg="mag", eeg=True, stim=True, eog=True)
...: raw.load_data()
Opening raw data file /home/adina/mne_data/MNE-sample-data/MEG/sample/sample_audvis_filt-0-40_raw.fif...
Read a total of 4 projection items:
PCA-v1 (1 x 102) idle
PCA-v2 (1 x 102) idle
PCA-v3 (1 x 102) idle
Average EEG reference (1 x 60) idle
Range : 6450 ... 48149 = 42.956 ... 320.665 secs
Ready.
Reading 0 ... 9009 = 0.000 ... 59.999 secs...
Out[2]: <Raw | sample_audvis_filt-0-40_raw.fif, 171 x 9010 (60.0 s), ~14.8 MB, data loaded>
In [3]: # high-pass filter the data and then perform ICA
...: filt_raw = raw.copy().filter(l_freq=1.0, h_freq=None)
...: ica = ICA(n_components=15, max_iter="auto", random_state=97)
...: ica.fit(filt_raw)
Filtering raw data in 1 contiguous segment
Setting up high-pass filter at 1 Hz
FIR filter parameters
Designing a one-pass, zero-phase, non-causal highpass filter:
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.0s remaining: 0.0s
[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.0s remaining: 0.0s
[Parallel(n_jobs=1)]: Done 3 out of 3 | elapsed: 0.0s remaining: 0.0s
[Parallel(n_jobs=1)]: Done 4 out of 4 | elapsed: 0.0s remaining: 0.0s
[Parallel(n_jobs=1)]: Done 161 out of 161 | elapsed: 0.1s finished
Fitting ICA to data using 161 channels (please be patient, this may take a while)
Selecting by number: 15 components
Fitting ICA took 0.5s.
Out[3]: <ICA | raw data decomposition, method: fastica (fit in 22 iterations on 9010 samples), 15 ICA components explaining 94.3 % of variance (161 PCA components available), channel types: mag, eeg, no sources marked for exclusion>
In [4]: gui = label_ica_components(raw, ica)
...:
...: # The
icaobject is modified to contain the component labels...: # after closing the GUI and can now be saved
...: # gui.close() # typically you close when done
...:
...: # Now, we can take a look at the components, which were modified in-place
...: # for the ICA instance.
...: print(ica.labels_)
ImportError Traceback (most recent call last)
Input In [4], in <cell line: 1>()
----> 1 gui = label_ica_components(raw, ica)
3 # The
icaobject is modified to contain the component labels4 # after closing the GUI and can now be saved
5 # gui.close() # typically you close when done
6
7 # Now, we can take a look at the components, which were modified in-place
8 # for the ICA instance.
9 print(ica.labels_)
File ~/repos/mne-icalabel/mne_icalabel/gui/init.py:26, in label_ica_components(inst, ica, show, block)
5 """Launch the IC labelling GUI.
6
7 Parameters
(...)
22 The graphical user interface (GUI) window.
23 """
24 from mne.viz.backends._utils import _init_mne_qtapp, _qt_app_exec
---> 26 from ._label_components import ICAComponentLabeler
28 # get application
29 app = _init_mne_qtapp()
File ~/repos/mne-icalabel/mne_icalabel/gui/_label_components.py:4, in
1 from typing import Dict, List, Union
3 from matplotlib import pyplot as plt
----> 4 from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg
5 from mne import BaseEpochs
6 from mne.io import BaseRaw
File ~/env/joss/lib/python3.9/site-packages/matplotlib/backends/backend_qt5agg.py:7, in
4 from .. import backends
6 backends._QT_FORCE_QT5_BINDING = True
----> 7 from .backend_qtagg import ( # noqa: F401, E402 # pylint: disable=W0611
8 _BackendQTAgg, FigureCanvasQTAgg, FigureManagerQT, NavigationToolbar2QT,
9 backend_version, FigureCanvasAgg, FigureCanvasQT
10 )
13 @_BackendQTAgg.export
14 class _BackendQT5Agg(_BackendQTAgg):
15 pass
File ~/env/joss/lib/python3.9/site-packages/matplotlib/backends/backend_qtagg.py:9, in
5 import ctypes
7 from matplotlib.transforms import Bbox
----> 9 from .qt_compat import QT_API, _enum, _setDevicePixelRatio
10 from .. import cbook
11 from .backend_agg import FigureCanvasAgg
File ~/env/joss/lib/python3.9/site-packages/matplotlib/backends/qt_compat.py:142, in
140 break
141 else:
--> 142 raise ImportError("Failed to import any qt binding")
143 else: # We should not get there.
144 raise AssertionError(f"Unexpected QT_API: {QT_API}")
ImportError: Failed to import any qt binding
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