passing functions into another function, resulting in ValueError

I want to create a function than can process my dataframe through two other functions and then create two new columns with the result. But i am stopped by a an error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

i do not know what is going on, as i am using the correct conditional "|"

import pandas as pd
import numpy as np
from numpy.random import randn
np.random.seed(101)

df = pd.DataFrame(randn(9,2),index='1 2 3 4 5 6 7 8 9'.split(),columns='a b'.split())


def bigger_than(df):
        #
        df = df.copy()
        df['a-true'] = np.where(df['a'] > 0, 1, 0)
        df['b-true'] = np.where(df['b'] > 0, 1, 0)
        return df


def less_than(df):
        df = df.copy()
        df['a-true'] = np.where(df['a'] < 0, 1, 0)
        df['b-true'] = np.where(df['b'] < 0, 1, 0)
        return df


def compare(df, func1, func2):
        df = df.copy()
        df['true'] = np.where(func1(df)['a-true'] == 0 | func1(df)['b-true'] == 0, 1, 0)
        df['true-again'] = np.where(func2(df)['a-true'] == 1 | func2(df)['b-true'] == 1, 1, 0)
        return df


print(compare(df, less_than, bigger_than))

Traceback (most recent call last):
  File "C:\Users\jeppe\PycharmProjects\pythonProject3\main.py", line 31, in <module>
    print(compare(df, less_than, bigger_than))
  File "C:\Users\jeppe\PycharmProjects\pythonProject3\main.py", line 26, in compare
    df['true'] = np.where(func1(df)['a-true'] == 0 | func1(df)['b-true'] == 0, 1, 0)
  File "C:\Users\jeppe\PycharmProjects\test\pythonProject3\lib\site-packages\pandas\core\generic.py", line 1537, in __nonzero__
    raise ValueError(
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

here is how you can do it in one line:

df['true'], df['true-again'] = (df['a'] >= 0) | (df['b'] >= 0), (df['a'] > 0) | (df['b'] > 0)

print(df)

output:

          a         b   true  true-again
1  1.048158  0.701041   True        True
2  0.835515 -1.614604   True        True
3  2.126922  0.421194   True        True
4 -1.409821 -0.045723  False       False
5 -1.553690  0.825518   True        True
6  0.596085  0.208414   True        True
7 -0.558074 -0.232004  False       False
8 -1.046353  0.737966   True        True
9  0.942001  1.733682   True        True