具有多个元素的数组的真值是模棱两可的错误？ Python

Question

from numpy import *
from pylab import *
from math import *

def TentMap(a,x):
    if x>= 0 and x<0.5:
        return 2.*a*x
    elif x>=0.5 and x<=1.:
        return 2.*a*(1.-x)

# We set a = 0.98, a typical chaotic value
a = 0.98
N = 1.0

xaxis = arange(0.0,N,0.01)

Func = TentMap

subplot(211)

title(str(Func.func_name) + ' at a=%g and its second iterate' %a)
ylabel('X(n+1)') # set y-axis label
plot(xaxis,Func(a,xaxis), 'g', antialiased=True)

subplot(212)

ylabel('X(n+1)') # set y-axis label
xlabel('X(n)')   # set x-axis label
plot(xaxis,Func(a,Func(a,xaxis)), 'bo', antialiased=True)  

My TentMap function isn't working properly. I keep getting the error The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() I don't understand how I'm supposed to use those. Basically, the TentMap function takes a value X and returns a certain value depending on what X is. So if 0<=x<0.5 then it returns 2 a x and if 0.5<=x<=1 then it returns 2 a (1-x).

Answer 1

If you compare a numpy array with a number, you'll get another array:

>>> from numpy import arange
>>> xaxis = arange(0.0, 0.04, 0.01)
>>> xaxis
array([ 0.  ,  0.01,  0.02,  0.03])
>>> xaxis <= .02
array([ True,  True,  True, False], dtype=bool)

The problem starts when you want to and this with something else, or use it in a boolean context:

>>> xaxis <= .02 and True
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

>>> bool(xaxis <= .02)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

And that's what you're trying to do in the constructor of your TentMap . Are you sure you don't need to use a where you're using x ?

Answer 2

You can use np.vectorize to get around this error which occurs when using and with a scalar value and arrray. The call looks like

np.vectorize(TentMap)(a,xaxis)