mindsponge.common.make_transform_from_reference

mindsponge.common.make_transform_from_reference(point_a, point_b, point_c)[source]

Using GramSchmidt process to construct rotation and translation from given points.

Calculate the rotation matrix and translation meets

point_b is the original point.
point_c is on the x_axis.
the plane a-b-c is on the x-y plane.

\begin{array}{r} \begin{aligned} {\vec{v}}_{1} = {\vec{x}}_{3} - {\vec{x}}_{2} \\ {\vec{v}}_{2} = {\vec{x}}_{1} - {\vec{x}}_{2} \\ {\vec{e}}_{1} = {\vec{v}}_{1} / | | {\vec{v}}_{1} | | \\ {\vec{u}}_{2} = {\vec{v}}_{2} - {\vec{e}}_{1} ({\vec{e}}_{1}^{T} {\vec{v}}_{2}) \\ {\vec{e}}_{2} = {\vec{u}}_{2} / | | {\vec{u}}_{2} | | \\ {\vec{e}}_{3} = {\vec{e}}_{1} \times {\vec{e}}_{2} \\ r o t a t i o n = ({\vec{e}}_{1}, {\vec{e}}_{2}, {\vec{e}}_{3}) \\ t r a n s l a t i o n = ({\vec{x}}_{2}) \end{aligned} \end{array}

Parameters

point_a (float, tensor) -> (tensor) – Spatial location information of atom 'N', shape is $[. . ., N_{r e s}, 3]$ .
point_b (float, tensor) -> (tensor) – Spatial location information of atom 'CA', shape is $[. . ., N_{r e s}, 3]$ .
point_c (float, tensor) -> (tensor) – Spatial location information of atom 'C', shape is $[. . ., N_{r e s}, 3]$ .

Returns

Tuple, rots $(x x, x y, x z, y x, y y, y z, z x, z y, z z)$ , the shape of every element is $(. . ., N_{r e s})$ .
Tuple, trans $(x, y, z)$ , the shape of every element is $(. . ., N_{r e s})$ .

Supported Platforms:: Ascend GPU

Examples

>>> import numpy as np
>>> import mindspore as ms
>>> from mindspore import Tensor
>>> from mindsponge.common.geometry import make_transform_from_reference
>>> input_0 = Tensor(np.ones((4, 256, 3)), ms.float32)
>>> input_1 = Tensor(np.ones((4, 256, 3)), ms.float32)
>>> input_2 = Tensor(np.ones((4, 256, 3)), ms.float32)
>>> rots, trans = make_transform_from_reference(input_0, input_1, input_2)
>>> print(len(rots), rots[0].shape, len(trans), trans[0].shape)
9, (4, 256), 3, (4, 256)