Q36 : np.ceil yield wrong answer

[zhukpm]

Q: Extract the integer part of a random array using 5 different methods
A:

...
print (np.ceil(Z)-1)
....

But it yields wrong results when float numbers have only integer part:

In[]:
Z = np.random.uniform(0,10,10)

Z = np.hstack([Z, [1., -1.]])

print (Z - Z%1)
print (np.floor(Z))
print (np.ceil(Z)-1)
print (Z.astype(int))
print (np.trunc(Z))

Out[]:
[ 4.  1.  2.  6.  0.  9.  0.  8.  4.  8.  1. -1.]
[ 4.  1.  2.  6.  0.  9.  0.  8.  4.  8.  1. -1.]
[ 4.  1.  2.  6.  0.  9.  0.  8.  4.  8.  0. -2.]
[ 4  1  2  6  0  9  0  8  4  8  1 -1]
[ 4.  1.  2.  6.  0.  9.  0.  8.  4.  8.  1. -1.]

Should be removed.

[rougier]

Oh, good point and I don't think it can be fixed easily (using ceil I mean). Maybe we can restrict the question to 4 methods. Can you make a PR ?

[zhukpm]

Oh, good point and I don't think it can be fixed easily (using ceil I mean). Maybe we can restrict the question to 4 methods. Can you make a PR ?

Sure.
By the way, there's also different behaviours when handling positive and negative numbers. See an example:

a = np.array([3.03, -3.03, 0.69, -0.69, 0., 1., -1.])
print(a)

print(a - a % 1)
print(np.floor(a))
print(np.ceil(a) - 1)
print(a.astype(int).astype(float))
print(np.trunc(a))

Results in

[ 3.03 -3.03  0.69 -0.69  0.    1.   -1.  ]
[ 3. -4.  0. -1.  0.  1. -1.]
[ 3. -4.  0. -1.  0.  1. -1.]
[ 3. -4.  0. -1. -1.  0. -2.]
[ 3. -3.  0.  0.  0.  1. -1.]
[ 3. -3.  0. -0.  0.  1. -1.]

So I suggest restrict it for positive numbers only and remove ceil. What do you think?