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 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])