Your example doesn't run, but here is one that does:
In [8]: x = np.array([50], dtype=float)
In [9]: np.piecewise(x, [0 < x <= 90, 90 < x <= 180], [1.1, 2.1])
array([ 1.1])
The answer to your second question is that it is returning an array
with the same dtype as its first argument.
The answer
On 2017/09/15 2:02 AM, Joe wrote:
Hello,
I have two questions and hope that you can help me.
1.)
Is np.piecewise only defined for two conditions or should something like
[0 < x <= 90, 90 < x <= 180, 180 < x <= 270]
also work?
2.)
Why does
np.piecewise(np.array([50]), [0 < x <= 90, 90 < x <=
Hello,
I have two questions and hope that you can help me.
1.)
Is np.piecewise only defined for two conditions or should something like
[0 < x <= 90, 90 < x <= 180, 180 < x <= 270]
also work?
2.)
Why does
np.piecewise(np.array([50]), [0 < x <= 90, 90 < x <= 180], [1.1, 2.1])
return [2] and
