Source: python-mne Version: 0.15.2+dfsg-2 Severity: serious https://tests.reproducible-builds.org/debian/rb-pkg/unstable/amd64/python-mne.html
... =================================== FAILURES =================================== ___________________ [doctest] mne.viz.misc.plot_ideal_filter ___________________ 840 .. versionadded:: 0.14 841 842 Examples 843 -------- 844 Plot a simple ideal band-pass filter:: 845 846 >>> from mne.viz import plot_ideal_filter 847 >>> freq = [0, 1, 40, 50] 848 >>> gain = [0, 1, 1, 0] 849 >>> plot_ideal_filter(freq, gain, flim=(0.1, 100)) #doctest: +ELLIPSIS Expected: <matplotlib.figure.Figure object at ...> Got: <Figure size 640x480 with 1 Axes> /build/1st/python-mne-0.15.2+dfsg/mne/viz/misc.py:849: DocTestFailure ________________________ test_plot_connectivity_circle _________________________ def test_plot_connectivity_circle(): """Test plotting connectivity circle """ import matplotlib.pyplot as plt node_order = ['frontalpole-lh', 'parsorbitalis-lh', 'lateralorbitofrontal-lh', 'rostralmiddlefrontal-lh', 'medialorbitofrontal-lh', 'parstriangularis-lh', 'rostralanteriorcingulate-lh', 'temporalpole-lh', 'parsopercularis-lh', 'caudalanteriorcingulate-lh', 'entorhinal-lh', 'superiorfrontal-lh', 'insula-lh', 'caudalmiddlefrontal-lh', 'superiortemporal-lh', 'parahippocampal-lh', 'middletemporal-lh', 'inferiortemporal-lh', 'precentral-lh', 'transversetemporal-lh', 'posteriorcingulate-lh', 'fusiform-lh', 'postcentral-lh', 'bankssts-lh', 'supramarginal-lh', 'isthmuscingulate-lh', 'paracentral-lh', 'lingual-lh', 'precuneus-lh', 'inferiorparietal-lh', 'superiorparietal-lh', 'pericalcarine-lh', 'lateraloccipital-lh', 'cuneus-lh', 'cuneus-rh', 'lateraloccipital-rh', 'pericalcarine-rh', 'superiorparietal-rh', 'inferiorparietal-rh', 'precuneus-rh', 'lingual-rh', 'paracentral-rh', 'isthmuscingulate-rh', 'supramarginal-rh', 'bankssts-rh', 'postcentral-rh', 'fusiform-rh', 'posteriorcingulate-rh', 'transversetemporal-rh', 'precentral-rh', 'inferiortemporal-rh', 'middletemporal-rh', 'parahippocampal-rh', 'superiortemporal-rh', 'caudalmiddlefrontal-rh', 'insula-rh', 'superiorfrontal-rh', 'entorhinal-rh', 'caudalanteriorcingulate-rh', 'parsopercularis-rh', 'temporalpole-rh', 'rostralanteriorcingulate-rh', 'parstriangularis-rh', 'medialorbitofrontal-rh', 'rostralmiddlefrontal-rh', 'lateralorbitofrontal-rh', 'parsorbitalis-rh', 'frontalpole-rh'] label_names = ['bankssts-lh', 'bankssts-rh', 'caudalanteriorcingulate-lh', 'caudalanteriorcingulate-rh', 'caudalmiddlefrontal-lh', 'caudalmiddlefrontal-rh', 'cuneus-lh', 'cuneus-rh', 'entorhinal-lh', 'entorhinal-rh', 'frontalpole-lh', 'frontalpole-rh', 'fusiform-lh', 'fusiform-rh', 'inferiorparietal-lh', 'inferiorparietal-rh', 'inferiortemporal-lh', 'inferiortemporal-rh', 'insula-lh', 'insula-rh', 'isthmuscingulate-lh', 'isthmuscingulate-rh', 'lateraloccipital-lh', 'lateraloccipital-rh', 'lateralorbitofrontal-lh', 'lateralorbitofrontal-rh', 'lingual-lh', 'lingual-rh', 'medialorbitofrontal-lh', 'medialorbitofrontal-rh', 'middletemporal-lh', 'middletemporal-rh', 'paracentral-lh', 'paracentral-rh', 'parahippocampal-lh', 'parahippocampal-rh', 'parsopercularis-lh', 'parsopercularis-rh', 'parsorbitalis-lh', 'parsorbitalis-rh', 'parstriangularis-lh', 'parstriangularis-rh', 'pericalcarine-lh', 'pericalcarine-rh', 'postcentral-lh', 'postcentral-rh', 'posteriorcingulate-lh', 'posteriorcingulate-rh', 'precentral-lh', 'precentral-rh', 'precuneus-lh', 'precuneus-rh', 'rostralanteriorcingulate-lh', 'rostralanteriorcingulate-rh', 'rostralmiddlefrontal-lh', 'rostralmiddlefrontal-rh', 'superiorfrontal-lh', 'superiorfrontal-rh', 'superiorparietal-lh', 'superiorparietal-rh', 'superiortemporal-lh', 'superiortemporal-rh', 'supramarginal-lh', 'supramarginal-rh', 'temporalpole-lh', 'temporalpole-rh', 'transversetemporal-lh', 'transversetemporal-rh'] group_boundaries = [0, len(label_names) / 2] node_angles = circular_layout(label_names, node_order, start_pos=90, group_boundaries=group_boundaries) con = np.random.RandomState(0).randn(68, 68) plot_connectivity_circle(con, label_names, n_lines=300, > node_angles=node_angles, title='test', ) con = array([[ 1.76405235, 0.40015721, 0.97873798, ..., -0.40178094, -1.63... 1.19712845, -1.63770629, ..., -1.35486121, -0.52109948, 1.88316415]]) group_boundaries = [0, 34] label_names = ['bankssts-lh', 'bankssts-rh', 'caudalanteriorcingulate-lh', 'caudalanteriorcingulate-rh', 'caudalmiddlefrontal-lh', 'caudalmiddlefrontal-rh', ...] node_angles = array([ 212.5, 327.5, 142.5, 397.5, 162.5, 377.5, 262.5, 277.5, ... 292.5, 167.5, 372.5, 217.5, 322.5, 132.5, 407.5, 192.5, 347.5]) node_order = ['frontalpole-lh', 'parsorbitalis-lh', 'lateralorbitofrontal-lh', 'rostralmiddlefrontal-lh', 'medialorbitofrontal-lh', 'parstriangularis-lh', ...] plt = <module 'matplotlib.pyplot' from '/usr/lib/python2.7/dist-packages/matplotlib/pyplot.pyc'> mne/viz/tests/test_circle.py:87: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ con = array([[ 1.76405235, 0.40015721, 0.97873798, ..., -0.40178094, -1.63... 1.19712845, -1.63770629, ..., -1.35486121, -0.52109948, 1.88316415]]) node_names = ['bankssts-lh', 'bankssts-rh', 'caudalanteriorcingulate-lh', 'caudalanteriorcingulate-rh', 'caudalmiddlefrontal-lh', 'caudalmiddlefrontal-rh', ...] indices = None, n_lines = 300 node_angles = array([ 3.70882466, 5.7159533 , 2.48709418, 6.93768378, 2.83616003, ...09112, 5.62868684, 2.31256126, 7.1122167 , 3.35975881, 6.06501915]) node_width = 0.087266462599715489, node_colors = None, facecolor = 'black' textcolor = 'white', node_edgecolor = 'black', linewidth = 1.5, colormap = 'hot' vmin = None, vmax = None, colorbar = True, title = 'test', colorbar_size = 0.2 colorbar_pos = (-0.3, 0.1), fontsize_title = 12, fontsize_names = 8 fontsize_colorbar = 8, padding = 6.0, fig = None, subplot = 111 interactive = True, node_linewidth = 2.0, show = True def plot_connectivity_circle(con, node_names, indices=None, n_lines=None, node_angles=None, node_width=None, node_colors=None, facecolor='black', textcolor='white', node_edgecolor='black', linewidth=1.5, colormap='hot', vmin=None, vmax=None, colorbar=True, title=None, colorbar_size=0.2, colorbar_pos=(-0.3, 0.1), fontsize_title=12, fontsize_names=8, fontsize_colorbar=8, padding=6., fig=None, subplot=111, interactive=True, node_linewidth=2., show=True): """Visualize connectivity as a circular graph. Note: This code is based on the circle graph example by Nicolas P. Rougier http://www.labri.fr/perso/nrougier/coding/. Parameters ---------- con : array Connectivity scores. Can be a square matrix, or a 1D array. If a 1D array is provided, "indices" has to be used to define the connection indices. node_names : list of str Node names. The order corresponds to the order in con. indices : tuple of arrays | None Two arrays with indices of connections for which the connections strenghts are defined in con. Only needed if con is a 1D array. n_lines : int | None If not None, only the n_lines strongest connections (strength=abs(con)) are drawn. node_angles : array, shape=(len(node_names,)) | None Array with node positions in degrees. If None, the nodes are equally spaced on the circle. See mne.viz.circular_layout. node_width : float | None Width of each node in degrees. If None, the minimum angle between any two nodes is used as the width. node_colors : list of tuples | list of str List with the color to use for each node. If fewer colors than nodes are provided, the colors will be repeated. Any color supported by matplotlib can be used, e.g., RGBA tuples, named colors. facecolor : str Color to use for background. See matplotlib.colors. textcolor : str Color to use for text. See matplotlib.colors. node_edgecolor : str Color to use for lines around nodes. See matplotlib.colors. linewidth : float Line width to use for connections. colormap : str Colormap to use for coloring the connections. vmin : float | None Minimum value for colormap. If None, it is determined automatically. vmax : float | None Maximum value for colormap. If None, it is determined automatically. colorbar : bool Display a colorbar or not. title : str The figure title. colorbar_size : float Size of the colorbar. colorbar_pos : 2-tuple Position of the colorbar. fontsize_title : int Font size to use for title. fontsize_names : int Font size to use for node names. fontsize_colorbar : int Font size to use for colorbar. padding : float Space to add around figure to accommodate long labels. fig : None | instance of matplotlib.pyplot.Figure The figure to use. If None, a new figure with the specified background color will be created. subplot : int | 3-tuple Location of the subplot when creating figures with multiple plots. E.g. 121 or (1, 2, 1) for 1 row, 2 columns, plot 1. See matplotlib.pyplot.subplot. interactive : bool When enabled, left-click on a node to show only connections to that node. Right-click shows all connections. node_linewidth : float Line with for nodes. show : bool Show figure if True. Returns ------- fig : instance of matplotlib.pyplot.Figure The figure handle. axes : instance of matplotlib.axes.PolarAxesSubplot The subplot handle. """ import matplotlib.pyplot as plt import matplotlib.path as m_path import matplotlib.patches as m_patches n_nodes = len(node_names) if node_angles is not None: if len(node_angles) != n_nodes: raise ValueError('node_angles has to be the same length ' 'as node_names') # convert it to radians node_angles = node_angles * np.pi / 180 else: # uniform layout on unit circle node_angles = np.linspace(0, 2 * np.pi, n_nodes, endpoint=False) if node_width is None: # widths correspond to the minimum angle between two nodes dist_mat = node_angles[None, :] - node_angles[:, None] dist_mat[np.diag_indices(n_nodes)] = 1e9 node_width = np.min(np.abs(dist_mat)) else: node_width = node_width * np.pi / 180 if node_colors is not None: if len(node_colors) < n_nodes: node_colors = cycle(node_colors) else: # assign colors using colormap node_colors = [plt.cm.spectral(i / float(n_nodes)) > for i in range(n_nodes)] E AttributeError: 'module' object has no attribute 'spectral' colorbar = True colorbar_pos = (-0.3, 0.1) colorbar_size = 0.2 colormap = 'hot' con = array([[ 1.76405235, 0.40015721, 0.97873798, ..., -0.40178094, -1.63... 1.19712845, -1.63770629, ..., -1.35486121, -0.52109948, 1.88316415]]) dist_mat = array([[ 1.00000000e+09, 2.00712864e+00, -1.22173048e+00, ..., 3...92497e+00, ..., 1.04719755e+00, -2.70526034e+00, 1.00000000e+09]]) facecolor = 'black' fig = None fontsize_colorbar = 8 fontsize_names = 8 fontsize_title = 12 i = 0 indices = None interactive = True linewidth = 1.5 m_patches = <module 'matplotlib.patches' from '/usr/lib/python2.7/dist-packages/matplotlib/patches.pyc'> m_path = <module 'matplotlib.path' from '/usr/lib/python2.7/dist-packages/matplotlib/path.pyc'> n_lines = 300 n_nodes = 68 node_angles = array([ 3.70882466, 5.7159533 , 2.48709418, 6.93768378, 2.83616003, ...09112, 5.62868684, 2.31256126, 7.1122167 , 3.35975881, 6.06501915]) node_colors = None node_edgecolor = 'black' node_linewidth = 2.0 node_names = ['bankssts-lh', 'bankssts-rh', 'caudalanteriorcingulate-lh', 'caudalanteriorcingulate-rh', 'caudalmiddlefrontal-lh', 'caudalmiddlefrontal-rh', ...] node_width = 0.087266462599715489 padding = 6.0 plt = <module 'matplotlib.pyplot' from '/usr/lib/python2.7/dist-packages/matplotlib/pyplot.pyc'> show = True subplot = 111 textcolor = 'white' title = 'test' vmax = None vmin = None mne/viz/circle.py:246: AttributeError ____________________________ test_plot_epochs_image ____________________________ def test_plot_epochs_image(): """Test plotting of epochs image.""" import matplotlib.pyplot as plt epochs = _get_epochs() epochs.plot_image(picks=[1, 2]) overlay_times = [0.1] epochs.plot_image(picks=[1], order=[0], overlay_times=overlay_times, vmin=0.01, title="test" ) epochs.plot_image(picks=[1], overlay_times=overlay_times, vmin=-0.001, vmax=0.001) assert_raises(ValueError, epochs.plot_image, picks=[1], overlay_times=[0.1, 0.2]) assert_raises(ValueError, epochs.plot_image, picks=[1], order=[0, 1]) assert_raises(ValueError, epochs.plot_image, axes=dict(), group_by=list(), combine='mean') assert_raises(ValueError, epochs.plot_image, axes=list(), group_by=dict(), combine='mean') with warnings.catch_warnings(record=True): # deprecated combine as str assert_raises(ValueError, epochs.plot_image, combine='error', picks=[1, 2]) assert_raises(ValueError, epochs.plot_image, units={"hi": 1}, scalings={"ho": 1}) epochs.load_data().pick_types(meg='mag') epochs.info.normalize_proj() with warnings.catch_warnings(record=True): # projs epochs.plot_image(group_by='type', combine='mean') epochs.plot_image(group_by={"1": [1, 2], "2": [1, 2]}, combine='mean') epochs.plot_image(vmin=lambda x: x.min()) assert_raises(ValueError, epochs.plot_image, axes=1, fig=2) ts_args = dict(show_sensors=False) with warnings.catch_warnings(record=True) as w: epochs.plot_image(overlay_times=[1.1], combine="gfp", ts_args=ts_args) assert_raises(ValueError, epochs.plot_image, combine='error', ts_args=ts_args) warnings.simplefilter('always') > assert_equal(len(w), 4) E AssertionError: E Items are not equal: E ACTUAL: 5 E DESIRED: 4 epochs = <Epochs | n_events : 1 (all good), tmin : -0.0998976065792 (s), tmax : 1.0006410259 (s), baseline : (None, 0), ~3.0 MB, data loaded> overlay_times = [0.1] plt = <module 'matplotlib.pyplot' from '/usr/lib/python2.7/dist-packages/matplotlib/pyplot.pyc'> ts_args = {'show_sensors': False} w = [<warnings.WarningMessage object at 0x7f3cef6c6990>, <warnings.WarningMessage object at 0x7f3cef6c68d0>, <warnings.War...x7f3cef6c6110>, <warnings.WarningMessage object at 0x7f3cef496290>, <warnings.WarningMessage object at 0x7f3cf050b650>] mne/viz/tests/test_epochs.py:147: AssertionError ____________________________ test_plot_annotations _____________________________ def test_plot_annotations(): """Test annotation mode of the plotter.""" raw = _get_raw() raw.info['lowpass'] = 10. with warnings.catch_warnings(record=True): # matplotlib > _annotation_helper(raw) raw = <Raw | test_raw.fif, n_channels x n_times : 9 x 14400 (24.0 sec), ~4.0 MB, data loaded> mne/viz/tests/test_raw.py:213: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ raw = <Raw | test_raw.fif, n_channels x n_times : 9 x 14400 (24.0 sec), ~4.0 MB, data loaded> def _annotation_helper(raw): """Helper for testing interactive annotations.""" import matplotlib.pyplot as plt n_anns = 0 if raw.annotations is None else len(raw.annotations.onset) fig = raw.plot() data_ax = fig.axes[0] fig.canvas.key_press_event('a') # annotation mode # modify description ann_fig = plt.gcf() for key in ' test': ann_fig.canvas.key_press_event(key) ann_fig.canvas.key_press_event('enter') ann_fig = plt.gcf() # XXX: _fake_click raises an error on Agg backend > _annotation_radio_clicked('', ann_fig.radio, data_ax.selector) E AttributeError: 'Figure' object has no attribute 'radio' ann_fig = <Figure size 450x275 with 0 Axes> data_ax = <matplotlib.axes._subplots.AxesSubplot object at 0x7f3d70a59390> fig = <Figure size 640x480 with 5 Axes> key = 't' n_anns = 0 plt = <module 'matplotlib.pyplot' from '/usr/lib/python2.7/dist-packages/matplotlib/pyplot.pyc'> raw = <Raw | test_raw.fif, n_channels x n_times : 9 x 14400 (24.0 sec), ~4.0 MB, data loaded> mne/viz/tests/test_raw.py:65: AttributeError =============================== warnings summary =============================== mne/decoding/tests/test_csp.py::test_csp /usr/lib/python2.7/dist-packages/matplotlib/contour.py:1173: UserWarning: No contour levels were found within the data range. warnings.warn("No contour levels were found" mne/viz/tests/test_epochs.py::test_plot_epochs_image /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) mne/viz/tests/test_ica.py::test_plot_ica_properties /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) mne/viz/tests/test_misc.py::test_plot_events /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) mne/viz/tests/test_topo.py::test_plot_topo_single_ch /usr/lib/python2.7/dist-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated; use an actual boolean (True/False) instead. warnings.warn(message, mplDeprecation, stacklevel=1) -- Docs: http://doc.pytest.org/en/latest/warnings.html ====== 4 failed, 448 passed, 270 skipped, 17 warnings in 2385.51 seconds ======= make[1]: *** [debian/rules:26: override_dh_auto_test] Error 1