ValueError: The truth value of array with more than one element is ambiguous. Use a.any() or a.all()

Question

I'm trying to iterate Numpy values, but I seem to be getting an error.

for ax in [ax1, ax2, ax3]:
   ax.axvline(enter_pos, c ='g')
   ax.axvline(exit_pos, c = 'r')

But I get this error:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

I know there are other answers on Stackover flow with this problem, but I have no idea what to do. The answers don't highlight how to change the code to accommodate a for loop, which is what has seem to have tripped me up.

I've tried:

ax in [ax1], ax in [ax2], ax in [ax3]

ax[ax1 & ax2 & ax3]

But nothing has worked yet.

Ideas?

* Edit *

Here is more of the code:

    ax1 = plt.subplot(311)
    data[[ticker[0], ticker[1]]].plot(ax = ax1)
    plt.ylabel('Price')
    plt.setp(ax1.get_xticklabels(), visible=False)

    ax2 = plt.subplot(312, sharex=ax1)
    results.spread.plot(ax=ax2, color='k')
    ax2.axhline(2, color='k')
    ax2.axhline(5, color='k')
    plt.ylabel('Spread')
    plt.setp(ax2.get_xticklabels(), visible=False)

    ax3 = plt.subplot(313, sharex=ax1)
    results.portfolio_value.plot(ax=ax3, color='k')
    plt.ylabel('Portfolio Value')

    # Plot spread enter and exit markers
    enter_pos = results.index[results.buy_spread]
    exit_pos = results.index[results.sell_spread]

    for ax in [ax1, ax2, ax3]:
        ax.axvline(enter_pos, c ='g')
        ax.axvline(exit_pos, c = 'r')

    plt.gcf().set_size_inches(16, 12)

* EDIT 2 *

I want to say the comment about the second loop is correct, but I still get the same error with this code:

for ax in [ax1, ax2, ax3]:
  for pos in enter_pos:
    ax.axvline(enter_pos, c ='g')
    ax.axvline(exit_pos, c = 'r')

Answer 1

axvline only support one number, you need a second loop:

for ax in [ax1, ax2, ax3]:
    for pos in enter_pos:
        ax.axvline(pos, c ='g')
    for pos in exit_pos:
        ax.axvline(pos, c ='r')

but if the size of enter_pos is large it maybe slow. You can use LineCollection istead, here is an example:

import pylab as pl
import numpy as np
from matplotlib import collections
from matplotlib import transforms

def axvlines(ax, x, **kw):
    from matplotlib import collections
    from matplotlib import transforms

    x = np.asanyarray(x)
    y0 = np.zeros_like(x)
    y1 = np.ones_like(x)        
    data = np.c_[x, y0, x, y1].reshape(-1, 2, 2)
    trans = transforms.blended_transform_factory(ax.transData, ax.transAxes)
    lines = collections.LineCollection(data, transform=trans, **kw)
    ax.add_collection(lines)

You can use it as:

axvlines(enter_pos, colors="g")
axvlines(exit_pos, colors="r")

By using axvlines(), you can even create a colormap for the lines:

X = np.logspace(-1, 0, 50)
fig, ax = pl.subplots()
axvlines(ax, X, cmap="jet", array=np.linspace(0, 1, 50))

Here is the output: