[SciPy-Dev] [ANN] Release of scikit-spatial package

[Tyler Reddy]

Some of the algorithms might be suitable for inclusion. Probably easier if
there's a nice paper / source for algorithm citation and it is clear that
we don't already have the functionality somewhere in SciPy.

To give one example, just browsing through, I see a collinearity algorithm.
Since collinearity is often used in the assessment of general position
prior to embarking on an algorithm in computational geometry,
it may be sensible to check if the low-level library we vendor for many
comp geo routines (Qhull) has a routine for this. Even if it does, it might
not be easy to expose directly, but it is a consideration I think.

Some of the operations, if ultimately suitable for inclusion, may fit in
the scipy.spatial.transform namespace, but probably case-by-case basis is
best in terms of assessing broad interest in the algorithm
and its suitability for inclusion.

On Mon, 8 Apr 2019 at 16:08, Andrew Hynes <andrewjhynes at gmail.com> wrote:

> Hi Stéfan,
>
>> This looks neat!  It reminds me a bit of the following book which I
>> enjoyed:
>>
>> http://www.geometricalgebra.net/
>>
>
> Thanks for the link - it looks like a good source for expanding the
> package.
>
> Can you tell us a bit more about how you see these functions typically
>> being applied in practice?
>>
> Sure, I can give an example from my masters project. It involved clinical
> gait analysis with a depth camera, so I used some of these functions to
> calculate gait parameters from positions in space.
>
> A basic walking stride consists of three positions: The initial swing
> foot, the stance foot, and the final swing foot. The stride length is the
> distance from the initial to final swing foot. The stride width is the
> length of the projection from the stance foot to the swing path (the line
> from the initial swing foot to the final).
>
> Here's a snippet of code using scikit-spatial to calculate gait parameters
> from three points: point_a_i (initial swing foot), point_b (stance foot),
> and point_a_f (final swing foot).
>
> from skspatial.objects import Vector, Line
>
> vector_a = Vector.from_points(point_a_i, point_a_f)
> line_a = Line(point=point_a_i, direction=vector_a)
>
> point_b_proj = line_a.project_point(point_b)
>
> stride_length = vector_a.norm()
> absolute_step_length = Vector.from_points(point_b, point_a_f).norm()
> step_length = Vector.from_points(point_b_proj, point_a_f).norm()
> stride_width = line_a.distance_point(point_b)
>
>
> Hopefully that gives an idea as to how the package can be used.
>
> Thanks,
>
> Andrew
>
> P. S. Great job on scikit-image!
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