This is because you cannot use and on numpy arrays. You need to replace the and with * and the or with + for numpy boolean arrays. (and do not forget to add parentheses).

In general, numpy arrays are very good at doing sensible things when you just write the code as if they were just numbers. Chaining comparisons is one of the rare exceptions. The error you're seeing is essentially this (obfuscated a bit by piecewise internals and ipython error formatting):

>>> a = np.array([1, 2, 3])
>>> 1.5 < a
array([False,  True,  True], dtype=bool)
>>> 
>>> 1.5 < a < 2.5
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()
>>> 
>>> (1.5 < a) & (a < 2.5)
array([False,  True, False], dtype=bool)
>>> 

You can alternatively use np.logical_and, but bitwise & (not and) works just fine here.

As far as plotting is concerned, numpy itself doesn't do any. Here's an example with matplotlib:

>>> import numpy as np
>>> def piecew(x):
...   conds = [x < 0, (x > 0) & (x < 1), (x > 1) & (x < 2), x > 2]
...   funcs = [lambda x: x+1, lambda x: 1, 
...            lambda x: -x + 2., lambda x: (x-2)**2]
...   return np.piecewise(x, conds, funcs)
>>>
>>> import matplotlib.pyplot as plt
>>> xx = np.linspace(-0.5, 3.1, 100)
>>> plt.plot(xx, piecew(xx))
>>> plt.show() # or plt.savefig('foo.eps')

Notice that piecewise is a capricious beast. In particular, it needs its x argument to be an array, and won't even try converting it if it isn't (in numpy parlance: x needs to be an ndarray, not an array_like):

>>> piecew(2.1)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 4, in piecew
  File "/home/br/.local/lib/python2.7/site-packages/numpy/lib/function_base.py", line 690, in piecewise
    "function list and condition list must be the same")
ValueError: function list and condition list must be the same
>>> 
>>> piecew(np.asarray([2.1]))
array([ 0.01])

you are passing a list to the function but you should pass a numpy array:

r1 = 1.8
r = numpy.arange(0, 3, 0.2)
print numpy.piecewise(r, [(r<r1), (r==r1), (r>r1)], [0, 1, 2])
# prints:
# array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  1.,  2.,  2.,  2., 2.,  2.])

but adding

r = list(r)
print numpy.piecewise(r, [(r<r1), (r==r1), (r>r1)], [0, 1, 2])

gives the error you mention.