I just tried this in Maya 2016 and 2018 and it worked in both, so perhaps 
this is all moot.
import maya.api.OpenMaya as om
q = om.MQuaternion()
print q
p = om.MQuaternion(0.7,0,0,0.7)
p.normalizeIt()
print p
print om.MQuaternion.slerp(p, q, 0.5, 0)
prints
(0, 0, 0, 1)
(0.707107, 0, 0, 0.707107)
(0.382683, 0, 0, 0.92388)
which is correct.



On Tuesday, 19 September 2017 07:57:55 UTC+10, Michael Boon wrote:
>
> If your dot is >0 in that code, and there are no mistakes, then you 
> shouldn't get a flip. If you're seeing a flip, my feeling is that you 
> should be looking for mistakes rather than worrying about the source of the 
> quaternions. You could print out some numbers.
> - I'd expect you to get a dot < 0.0 from quaternions-from-matrices 
> sometimes, even though neither matrix can be >180, for example, two 
> matrices that represent rotations of +100 and -100 degrees, their 
> difference would be 200.
> - f_theta should be half of the angle between your matrices (in radians). 
> Try some tests with simple rotations and see if it looks correct. It should 
> always be between 0 and pi/2 (90 degrees).
>
> You call negateIt() on m_quaternion_2. That changes the quat in-place. So 
> even outside the function, m_quaternion_2 will be different, which possibly 
> causes trouble. You could try inverting it differently, perhaps invert 
> f_scale_2 instead since that will have the same effect.
>
> Apart from that, I can't see anything wrong with your code.
>
>
>
>
> On 18 September 2017 at 18:08, Rémi Deletrain <remi.deletr...@gmail.com> 
> wrote:
>
>> Ho I'm sorry ... I just see that the code I sent was not the right one 
>> ... I did some testing and suddenly the code had become anything ...
>>
>> def slerp_quaternion(m_quaternion_1, m_quaternion_2, f_weight):
>>
>>     """
>>     !@Brief Apply Spherical interpolation between two quaternions.
>>
>>     @type m_quaternion_1: OpenMaya.MQuaternion
>>     @param m_quaternion_1: First Quaternion.
>>     @type m_quaternion_2: OpenMaya.MQuaternion
>>     @param m_quaternion_2: Second Quaternion.
>>     @type f_weight: float
>>     @param f_weight: Value for blending.
>>     """
>>
>>     #   Normalize quaternions
>>     m_quaternion_1 = m_quaternion_1.normal()
>>     m_quaternion_2 = m_quaternion_2.normal()
>>
>>     #   If is equial return first quaternion
>>     if m_quaternion_1.isEquivalent(m_quaternion_2):
>>         return m_quaternion_1
>>
>>     # TODO: fixlater
>>     # If the inputs are too close for comfort,
>>     # linearly interpolate and normalize the result.
>>     # if abs(dot) > 0.9995:
>>     #     pass
>>
>>     # If the dot product is negative, the quaternions
>>     # have opposite handed-ness and slerp won't take
>>     # the shorter path. Fix by reversing one quaternion.
>>     # dot = dot_product(m_quaternion_1, m_quaternion_2)
>>     dot = dot_product(m_quaternion_1, m_quaternion_2)
>>     if dot < 0.0:
>>         m_quaternion_2.negateIt()
>>         dot *= -1.0
>>
>>     #   Weight Blend
>>     f_scale_1 = 1.0 - f_weight
>>     f_scale_2 = f_weight
>>
>>     #   Get Quaternion median
>>     dot = max(min(dot, 1.0), -1.0)
>>     f_theta = math.acos(dot)
>>     f_sin_theta = math.sin(f_theta)
>>
>>     f_scale_1 = math.sin(f_scale_1 * f_theta) / f_sin_theta
>>     f_scale_2 = math.sin(f_scale_2 * f_theta) / f_sin_theta
>>
>>     #   New Quaternion
>>     a_new_values = []
>>     for i in xrange(4):
>>         a_new_values.append(f_scale_1 * m_quaternion_1[i] + f_scale_2 * 
>> m_quaternion_2[i])
>>
>>     return OpenMaya.MQuaternion(a_new_values[0], a_new_values[1], 
>> a_new_values[2], a_new_values[3])
>>
>>
>> I do not get a better result. I wanted to use the function slerp of maya 
>> but it is accessible only in c ++ not in python. So I make a slerp function 
>> in python. The current problem is that as I can not know if my dot is 
>> positive or negative. So I have a flip of 180 that is done on my rotation. 
>> I understand better now with your explanation. I use the matrices to 
>> retrieve quaternions. So I would have to retrieve the quaternions since the 
>> euler rotations?
>>
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