from mne import Epochs, find_events
from mne.datasets import sample
from mne.io import read_raw_fif
from mne.viz import plot_evoked_topo


directory = sample.data_path()
fname = directory / "MEG" / "sample" / "sample_audvis_filt-0-40_raw.fif"
raw = read_raw_fif(fname, preload=False)
raw.pick(("eeg", "stim")).load_data()
events = find_events(raw)
epochs = Epochs(raw, events, dict(cond1=1, cond2=2), tmin=-0.2, tmax=0.5, preload=True)
evokeds = {"cond1": epochs["cond1"].average(), "cond2": epochs["cond2"].average()}
fig = plot_evoked_topo(
    [evokeds["cond1"], evokeds["cond2"]],
    color=["#3498DB", "gray"],
    vline=[0, 0.080],
)

Traceback (most recent call last):
  File "c:\Users\scheltie\pyvenv\mscheltienne\mne-python\lib\site-packages\matplotlib\cbook.py", line 298, in process
    func(*args, **kwargs)
  File "C:\Users\scheltie\git\mscheltienne\mne-python\mne\viz\topo.py", line 380, in _plot_topo_onpick
    show_func(ax, ch_idx)
  File "C:\Users\scheltie\git\mscheltienne\mne-python\mne\viz\topo.py", line 635, in _plot_timeseries
    plt.axvline(vline, color=hvline_color, linewidth=1.0, linestyle="--")
  File "c:\Users\scheltie\pyvenv\mscheltienne\mne-python\lib\site-packages\matplotlib\pyplot.py", line 2716, in axvline
    return gca().axvline(x=x, ymin=ymin, ymax=ymax, **kwargs)
  File "c:\Users\scheltie\pyvenv\mscheltienne\mne-python\lib\site-packages\matplotlib\axes\_axes.py", line 849, in axvline
    scalex = (xx < xmin) or (xx > xmax)
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()