mindsponge.common
API Name |
Description |
Supported Platforms |
Find optimal renaming for ground truth that maximizes LDDT. |
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Align two protein fasta sequence. |
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Put in a pdb file and get fasta information from it. |
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get atom positions, residue index etc. |
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The function of transforming sparse encoding method to densely encoding method. |
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mindsponge.common.geometry
API Name |
Description |
Supported Platforms |
Rotate and translate the input coordinates. |
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Initialize quaternion, rotation, translation of affine. |
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The inverse transformation of a rigid body group transformation with respect to a point coordinate, that is, the inverse transformation of apply to point Make rotational translation changes on coordinates with the transpose of the rotation matrix \((xx, xy, xz, yx, yy, yz, zx, zy, zz)\) and the translation vector \((x, y, z)\) translation. |
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Computes group inverse of rigid transformations. |
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Computes inverse of rotations \(m\). |
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Using GramSchmidt process to construct rotation and translation from given points. |
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Return a new QuatAffine which applies the transformation update first. |
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Create quat affine representations based on rots and trans. |
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Multiply a quaternion by a pure-vector quaternion. |
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Convert a normalized quaternion to a rotation matrix. |
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Take the input 'tensor' \([(xx, xy, xz, yx, yy, yz, zz)]\) to get the new 'quaternion', 'rotation', 'translation'. |
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Change quaternion to tensor. |
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Gram-Schmidt process. |
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Change rigid \(b\) from its local coordinate system to rigid \(a\) local coordinate system, using rigid rotations and translations. |
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Numpy version of getting results rigid \(x\) multiply rotations \(\vec y\) . |
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Transform vector \(\vec v\) to rigid' local coordinate system. |
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Adds an additional dimension to rots at the given axis. |
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Amortize and split the 3*3 rotation matrix corresponding to the last two axes of input Tensor to obtain each component of the rotation matrix, inverse of 'rots_to_tensor'. |
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Put in two vectors \(\vec a = (a_x, a_y, a_z)\) and \(\vec b = (b_x, b_y, b_z)\). |
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Get result of rotation matrix x multiply rotation matrix y. |
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Apply rotations \(\vec m = (m_0, m_1, m_2, m_3, m_4, m_5, m_6, m_7, m_8)\) to vectors \(\vec v = (v_0, v_1, v_2)\). |
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Scaling of rotation matrixs. |
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Translate rots represented by vectors to tensor, inverse of 'rots_from_tensor'. |
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Cross product of vectors \(v_1 = (x_1, x_2, x_3)\) and \(v_2 = (y_1, y_2, y_3)\). |
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Dot product of vectors \(v_1 = (x_1, x_2, x_3)\) and \(v_2 = (y_1, y_2, y_3)\). |
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Add an extra dimension to the input v at the given axis. |
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Get vectors from the last axis of input tensor. |
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Calculate the l2-norm of a vector. |
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Use l2-norm normalization vectors |
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Scale the vector. |
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Subtract two vectors. |
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Converts 'v' to tensor with last dim shape 3, inverse of 'vecs_from_tensor'. |
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