Q:

matplotlib axvline truth ambiguous or list issue?

I'm trying to plot some vertical lines on a chart that has a "list" of integers (1...300) and some "values" (floats).  The following works when x=[48], but when x is set to x=[48, 83, 155, 292], the following code:
pylab.plot(list, values, label='Trend', color='k', linestyle='-')
pylab.axvline(x, linewidth=1, color='g')

Generates this error:
  File "/usr/lib/pymodules/python2.7/matplotlib/pyplot.py", line 2053, in axvline
    ret = ax.axvline(x, ymin, ymax, **kwargs)   File "/usr/lib/pymodules/python2.7/matplotlib/axes.py", line 3478, 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()

What does it mean?  (I thought it was pretty funny that python pretends to knows when truth is ambiguous).  Can I not pass a list to axvline?

A:

No, you can't pass a list to axvline. For multiple vertical lines within one line, something like this will do
[pylab.axvline(_x, linewidth=1, color='g') for _x in x]

A:

For completeness, there is also the possibility of using matplotlib.pyplots vlines. This function accepts a list of x-coordinates. Furthermore, you can specify where the lines need to start/end with the arguments ymin and ymax. In the case of this question the code would be:
import matplotlib.transforms as mt

fig, ax = plt.subplots()
ax.plot(list, values, label='Trend', color='k', linestyle='-')

trans = mt.blended_transform_factory(ax.transData, ax.transAxes)
ax.vlines(x, ymin=0, ymax=1, linewidth=1, color='g', transform=trans)

Using the transform argument makes it easier to have the lines from the top to the bottom of your plot. You can read more about it here. You can also skip that argument. In that case you have to specify ymin and ymax in actual y-coordinates.

A:

Instead of multiple calls to axvline we can use the plot command itself but providing the correct transformation (this is many times faster if there are many lines):
import matplotlib.transforms as tx
ax = pylab.gca()
trans = tx.blended_transform_factory(ax.transData, ax.transAxes)
pylab.plot(np.repeat(x, 3), np.tile([.25, .75, np.nan], len(x)), linewidth=2, color='g', transform=trans)

