Wrench.by_samples

classmethod Wrench.by_samples(wrenches, proportion_to_cut=0.1)[source]

Construct the wrench by sampled data, allowing to filter.

Parameters:

wrencheslist of Wrench: List of wrenches.
proportion_to_cutfloat: Fraction to cut off of both tails of the distribution

Returns:

Wrench: The mean wrench after trimming distribution from both tails.

Examples

>>> w1 = Wrench([1, 1, 1], [.1,.1,.1])
>>> w2 = Wrench([2, 2, 2], [.2,.2,.2])
>>> w3 = Wrench([3, 3, 3], [.3,.3,.3])
>>> w = Wrench.by_samples([w1, w2, w3])
>>> print(w.force)
Vector(x=2.000, y=2.000, z=2.000)
>>> print(w.torque)
Vector(x=0.200, y=0.200, z=0.200)